This paper takes up David Gauthier's most recent defense of the rationality of cooperation in prisoner's dilemmas. In that defense, Gauthier argues for a Pareto-optimizing theory of rational choice. According to Gauthier, rational action should sometimes aim at Pareto-optimization, and cooperation in prisoner's dilemmas is rational because it is Pareto-optimizing. I argue that Pareto-optimization cannot justify cooperation in the prisoner's dilemma in a manner that is also consistent with Gauthier's other desiderata. Either: the rationality (...) of cooperation must derive from what is beneficial for the group rather than what is beneficial for the individual, leaving the individual qua individual without any reason to cooperate, or Gauthier cannot explain why defecting in prisoner's dilemmas is not also rational. (shrink)

In a recent article, Gauthier rejects orthodox rational choice contractarianism in favor of a revisionist approach to the social contract that, according to him, justifies his principle of maximin proportionate gain as a principle of distributive justice. I agree with Gauthier that his principle of maximin proportionate gain cannot be justified by orthodox rational choice contractarianism. I argue, however, that orthodox rational choice contractarianism, before and after Gauthier, is still a viable approach to the social contract, although the scope of (...) this approach is limited. Orthodox rational choice contractarianism can be applied fruitfully to moral philosophy only in situations of deep moral pluralism in which moral reasoning is reduced to instrumental reasoning, because the members of society do not share, as assumed by traditional moral theories, a consensus on moral ideals as traditionally conceived as a starting point for the derivation of moral rules but only an overarching end that they aim to reach. If orthodox rational choice contractarianism is applied adequately, then it offers a viable approach to the social contract that, in contrast to Gauthier’s theory, justifies a rival principle for distributive conflicts that is valid for deeply morally pluralistic societies. (shrink)

The Pareto principle states that if the members of society express the same preference judgment between two options, this judgment is compelling for society. A building block of normative economics and social choice theory, and often borrowed by contemporary political philosophy, the principle has rarely been subjected to philosophical criticism. The paper objects to it on the ground that it indifferently applies to those cases in which the individuals agree on both their expressed preferences and their reasons for entertaining (...) them, and those cases in which they agree on their expressed preferences, while differing on their reasons. The latter are cases of "spurious unanimity", and it is normatively inappropriate, or so the paper argues, to defend unanimity preservation at the social level for them, so the Pareto principle is formulated much too broadly. The objection seems especially powerful when the principle is applied in an ex ante context of uncertainty, in which individuals can disagree on both their probabilities and utilities, and nonetheless agree on their preferences over prospects. (shrink)

Suppose a driverless car encounters a scenario where harm to at least one person is unavoidable and a choice about how to distribute harms between different persons is required. How should the driverless car be programmed to behave in this situation? I call this the moral design problem. Santoni de Sio defends a legal-philosophical approach to this problem, which aims to bring us to a consensus on the moral design problem despite our disagreements about which moral principles provide the correct (...) account of justified harm. He then articulates an answer to the moral design problem based on the legal doctrine of necessity. In this paper, I argue that Santoni de Sio’s answer to the moral design problem does not achieve the aim of the legal-philosophical approach. This is because his answer relies on moral principles which, at least, utilitarians have reason to reject. I then articulate an alternative reading of the doctrine of necessity, and construct a partial answer to the moral design problem based on this. I argue that utilitarians, contractualists and deontologists can agree on this partial answer, even if they disagree about which moral principles offer the correct account of justified harm. (shrink)

A large number of engineering problems involve several conflicting objectives, which today are often solved through expensive simulation calculations. Methods based on meta-models are one of the approaches to solving this group of problems. In this paper, multiobjective optimization in the extraction system of a copper open-pit mine complex is presented by the modified-NBI optimization method and regression meta-model. For this purpose, two objective functions of maximizing the amount of total extraction, which is the sum of the extraction (...) of sulfide, oxide, low-grade ores, and waste in this mine, and minimizing the transport time of haulage according to the limitation of its storage capacity, transport equipment, and budget are considered. The Central Composite Design method is used to build the Design of Experiments for the design variables. The considered design variables are the number of trucks of 120 tons, 240 tons, 35 tons, and 100 tons. The number of targets considered in each design combination is considered the response surface. The suitable meta-model to maximize the total extraction rate and minimize the transport time of the haulage, two modified functions of nonlinear regression have been determined. The accuracy of the models for selection has been done using PRESS and R 2 statistics. The most common PRESS error has also been used to validate the meta-models. Then the multiobjective optimization problem was solved using the modified-NBI method. Finally, Pareto and optimal solutions using the proposed approach were presented and discussed. (shrink)

Model predictive control technology can effectively reduce the bad effect caused by inaccurate data prediction in microgrid energy management problem. However, the use of MPC technology needs to dynamically select an optimal solution from the Pareto solution set to implement, which needs the participant of the decision-makers frequently. In order to reduce the burden on decision-makers, we designed a knee point-based evolutionary multiobjective optimization algorithm, termed KBEMO. Knee point is the solution on Pareto front with the maximum (...) marginal utility, which is considered as the preferred solution if there is no other preference. This algorithm focuses on obtaining the knee region and automatically outputs knee points after the optimization. By combining this algorithm with MPC technology, it can effectively reduce the amount of computational consumption and obtain better convergence. Experimental results show that this method is more competitive than the traditional single-objective MPC method. (shrink)

Evolutionary multi-objective optimization algorithms have been successfully applied in many real-life problems. EMOAs approximate the set of trade-offs between multiple conflicting objectives, known as the Pareto optimal set. Reference point approaches can alleviate the optimization process by highlighting relevant areas of the Pareto set and support the decision makers to take the more confident evaluation. One important drawback of this approaches is that they require an in-depth knowledge of the problem being solved in order to function (...) correctly. Collective intelligence has been put forward as an alternative to deal with situations like these. This paper extends some well-known EMOAs to incorporate collective preferences and interactive techniques. Similarly, two new preference-based multi-objective optimization performance indicators are introduced in order to analyze the results produced by the proposed algorithms in the comparative experiments carried out. (shrink)

In order to solve the shortcomings of particle swarm optimization in solving multiobjective optimization problems, an improved multiobjective particle swarm optimization algorithm is proposed. In this study, the competitive strategy was introduced into the construction process of Pareto external archives to speed up the search process of nondominated solutions, thereby increasing the speed of the establishment of Pareto external archives. In addition, the descending order of crowding distance method is used to limit the size of (...) external archives and dynamically adjust particle parameters; in order to solve the problem of insufficient population diversity in the later stage of algorithm iteration, time-varying Gaussian mutation strategy is used to mutate the particles in external archives to improve diversity. The simulation experiment results show that the improved algorithm has better convergence and stability than the other compared algorithms. (shrink)

In chapter four of Anarchy, State, and Utopia, Robert Nozick raised interesting questions about whether or not it is ever morally acceptable to act against what are agreed to be an individual's natural moral rights. The pursuit of these questions opens up issues concerning the specific content of these individual rights. This essay explores Nozick's questions by posing examples and using our considered responses to them to specify the shape of individual rights. The exploration provisionally concludes that a conception (...) of individual moral rights quite different from Nozick's looks attractive and merits further development. Footnotesa I thank Ellen Frankel Paul for helpful, constructive, and substantive comments on a prior draft of this essay. It goes without saying that her comments outstripped my ability to respond. (shrink)

The economical/environmental scheduling problem of the ship integrated energy system has high computational complexity, which includes more than one optimization objective, various types of constraints, and frequently fluctuated load demand. Therefore, the intelligent scheduling strategies cannot be applied to the ship energy management system online, which has limited computing power and storage space. Aiming at realizing green computing on SEMS, in this paper a typical SIES-EESP optimization model is built, considering the form of decision vectors, the economical/environmental (...) class='Hi'>optimization objectives, and various types of real-world constraints of the SIES. Based on the complexity of SIES-EESPs, a two-stage offline-to-online multiobjective optimization strategy for SIES-EESP is proposed, which transfers part of the energy dispatch online computing task to the offline high-performance computer systems. The specific constraints handling methods are designed to reduce both continuous and discrete constraints violations of SIES-EESPs. Then, an establishment method of energy scheduling scheme-base is proposed. By using the big data offline, the economical/environmental scheduling solutions of a typical year can be obtained and stored with more computing resources and operation time on land. Thereafter, a short-term multiobjective offline-to-online optimization approach by SEMS is considered, with the application of multiobjective evolutionary algorithm and typical schemes corresponding to the actual SIES-EESPs. Simulation results show that the proposed strategy can obtain enough feasible Pareto solutions in a shorter time and get well-distributed Pareto sets with better convergence performance, which can well adapt to the features of real-world SIES-EESPs and save plenty of operation time and storage space for the SEMS. (shrink)

v. 1. Lo sviluppo del capitalismo (1872-1895).--v. 2. Reazione, liberta, fascismo (1896-1923).

In multimodal multiobjective optimization problems, multiple Pareto optimal sets, even some good local Pareto optimal sets, should be reserved, which can provide more choices for decision-makers. To solve MMOPs, this paper proposes an evolutionary algorithm with clustering-based assisted selection strategy for multimodal multiobjective optimization, in which the addition operator and deletion operator are proposed to comprehensively consider the diversity in both decision and objective spaces. Specifically, in decision space, the union population is partitioned into multiple clusters (...) by using a density-based clustering method, aiming to assist the addition operator to strengthen the population diversity. Then, a number of weight vectors are adopted to divide population into N subregions in objective space. Moreover, in the deletion operator, the solutions in the most crowded subregion are first collected into previous clusters, and then the worst solution in the most crowded cluster is deleted until there are N solutions left. Our algorithm is compared with other multimodal multiobjective evolutionary algorithms on the well-known benchmark MMOPs. Numerical experiments report the effectiveness and advantages of our proposed algorithm. (shrink)

For the application of the standard genetic algorithm in illustration art design, there are still problems such as low search efficiency and high complexity. This paper proposes an illustration art design model based on operator and clustering optimization genetic algorithm. First, during the operation of the genetic algorithm, the values of the crossover probability and the mutation probability are dynamically adjusted according to the characteristics of the population to improve the search efficiency of the algorithm, then the k-medoids algorithm (...) is introduced to optimize the clustering of the genetic algorithm, and a cost function is used to carry out and evaluate the quality of clustering to optimize the complexity of the original algorithm. In addition, a multiobjective optimization genetic algorithm with complex constraints based on group classification is proposed. This algorithm focuses on the problem of group diversity and uses k-means cluster analysis operation to solve the problem of group diversity. The algorithm divides the entire group into four subgroups and assigns appropriate fitness values to reflect the optimal preservation strategy. A large number of computer simulation calculations show that the algorithm can obtain a widely distributed and uniform Pareto optimal solution, the evolution speed is fast, usually only a few iterations can achieve a good optimization effect, and finally the improved genetic algorithm is used to design the random illustration art. The example simulation shows that the improved algorithm proposed in this paper can achieve higher artistic and innovative illustration art design. (shrink)

The constraint-handling methods using multiobjective techniques in evolutionary algorithms have drawn increasing attention from researchers. This paper proposes an efficient conical area differential evolution algorithm, which employs biased decomposition and dual populations for constrained optimization by borrowing the idea of cone decomposition for multiobjective optimization. In this approach, a conical subpopulation and a feasible subpopulation are designed to search for the global feasible optimum, along the Pareto front and the feasible segment, respectively, in a cooperative way. In (...) particular, the conical subpopulation aims to efficiently construct and utilize the Pareto front through a biased cone decomposition strategy and conical area indicator. Neighbors in the conical subpopulation are fully exploited to assist each other to find the global feasible optimum. Afterwards, the feasible subpopulation is ranked and updated according to a tolerance-based rule to heighten its diversity in the early stage of evolution. Experimental results on 24 benchmark test cases reveal that CADE is capable of resolving the constrained optimization problems more efficiently as well as producing solutions that are significantly competitive with other popular approaches. (shrink)

Vilfredo Pareto's Manual of Political Economy is a 'classic' study in the history of economic thought. It is not only one of the leading works in the Lausanne tradition of economics, which centres on the theory of general equilibrium, it is one of the most important books in the history of neoclassical economics. This 'critical edition' of Pareto's Manual of Political Economy is a very significant work for two main reasons. First, it is the only variorum translation of (...) the 1906 Italian language Manuale di Economia Politica and the 1909 French language Manuel d'Économie Politique. Second, it includes extensive contributions by the editors, all of whom are authorities on the work of Pareto. It total, the editorial contribution are around two hundred pages and range from brief annotations, to extended editors' notes and detailed notes on the 1909 mathematical appendix. (shrink)

Social robotics has a high disruptive potential, for it expands the field of application of intelligent technology to practical contexts of a relational nature. Due to their capacity to “intersubjectively” interact with people, social robots can take over new roles in our daily activities, multiplying the ethical implications of intelligent robotics. In this paper, we offer some preliminary considerations for the ethical reflection on social robotics, so that to clarify how to correctly orient the critical-normative thinking in this arduous task. (...) We defend the ‘being perspective’ and its linked categories of ‘teleology’ and ‘interest’ as the ones from which to articulate the reflection. We argue that attending primarily to the ‘being’, before the ‘doing’, of robots allow us to correctly approach the core phenomenon of all ethical concerns on social robotics, avoiding the reductionisms in the ethical gaze to which the latter may lead. (shrink)

Many real-world problems entail multiple conflicting objectives, which makes multiobjective optimization an important subject. Much attention has been paid to Genetic Algorithm as a potent multiobjective optimization method, and the effectiveness of its hybridization with local search has recently been reported in the literature. However, there have been a relatively small number of studies on LS methods for multiobjective function optimization. Although each of the existing LS methods has some strong points, they have respective drawbacks such as (...) high computational cost and inefficiency of improving objective functions. Hence, a more effective and efficient LS method is being sought, which can be used to enhance the performance of the hybridization. Pareto descent directions are defined in this paper as descent directions to which no other descent directions are superior in improving all objective functions. Moving solutions in such directions is expected to maximally improve all objective functions simultaneously. This paper proposes a new LS method, Pareto Descent Method, which finds Pareto descent directions and moves solutions in such directions. In the case part or all of them are infeasible, it finds feasible Pareto descent directions or descent directions as necessary and moves solutions in these directions. PDM finds these directions by solving linear programming problems. Thus, it is computationally inexpensive. Experiments have shown that PDM is superior to existing methods. (shrink)

Function optimization underlies many real-world problems and hence is an important research subject. Most of the existing optimization methods were developed to solve primarily unconstrained problems. Since real-world problems are often constrained, appropriate handling of constraints is necessary in order to use the optimization methods. In particular, the performances of some methods such as Genetic Algorithms can be substantially undermined by ineffective constraint handling. Despite much effort devoted to the studies of constraint-handling methods, it has been reported (...) that each of them has certain limitations. Hence, further studies for designing more effective constraint-handling methods are needed. For this reason, we investigated the guidelines for a method to effectively handle constraints. The guidelines are that the method 1) takes the approach of repair operators, 2) monotonically decreases both the number of violated constraints and constraint violations, and 3) searches over the boundaries of violated constraints. Based on these guidelines, we designed a new constraint-handling method Pareto Descent Repair operator in which ideas derived from multi-objective local search and gradient projection method are incorporated. Experiments comparing GA that use PDR and some of the existing constraint-handling methods confirmed the effectiveness of PDR. (shrink)

In a 2013 article, David Gauthier noted upon the twenty-fifth anniversary of the publication of Morals by Agreement that his contractarian approach to morality had found a niche among ‘some of those who remain unpersuaded by either Kantianism or utilitarianism’. In this article I will focus on Pareto optimization and I will argue that the Gauthier contract, even in spite of the article’s revisions, is still less useful for consultation purposes than Gauthier is assuming. To highlight the conceptual (...) distance that I think separates the Gauthier contract from real-world circumstances—a separation that is greater than Gauthier supposes—I will focus on the problem of ‘civic defection’. The point is not for us to repudiate as such the deliverances of the Gauthier model, but simply to use caution in our deployment of the model, and, in order to access the full extent of the model’s offerings, to resist the temptation to deploy it in the service of purposes which it is not capable of accomplishing. (shrink)

This paper studies a special scheduling problem under hierarchical management in nurse staff. This is a more complex rostering problem than traditional nurse scheduling. The first is that the rostering requirements of charge nurses and general nurses are different under hierarchical management. The second is that nurses are preferable for relative fair rather than absolute fair under hierarchical management. The model aims at allocating the required workload to meet the operational requirements, weekend rostering preferences, and relative fairness preferences. Two hybrid (...) heuristic algorithms based on multiobjective grey wolf optimizer and three corresponding single heuristic algorithms are employed to solve this problem. The experimental results based on real cases from the Third People’s Hospital, Panzhihua, China, show that MOGWO does not as good as it does on other engineering optimization. However, the hybrid algorithms based on MOGWO are better than corresponding single algorithms on generational distance and spacing of Pareto solutions. Furthermore, for relative fair rostering objective, NSGAII-MOGWO has more power to find the optimal solution in the dimension of relative fairness. (shrink)

Recently, decomposition-based multiobjective evolutionary algorithms have good performances in the field of multiobjective optimization problems and have been paid attention by many scholars. Generally, a MOP is decomposed into a number of subproblems through a set of weight vectors with good uniformly and aggregate functions. The main role of weight vectors is to ensure the diversity and convergence of obtained solutions. However, these algorithms with uniformity of weight vectors cannot obtain a set of solutions with good diversity on some (...) MOPs with complex Pareto optimal fronts. To deal with this problem, an improved decomposition-based multiobjective evolutionary algorithm with adaptive weight adjustment is proposed. Firstly, a new method based on uniform design and crowding distance is used to generate a set of weight vectors with good uniformly. Secondly, according to the distances of obtained nondominated solutions, an adaptive weight vector adjustment strategy is proposed to redistribute the weight vectors of subobjective spaces. Thirdly, a selection strategy is used to help each subobjective space to obtain a nondominated solution. Comparing with six efficient state-of-the-art algorithms, for example, NSGAII, MOEA/D, MOEA/D-AWA, EMOSA, RVEA, and KnEA on some benchmark functions, the proposed algorithm is able to find a set of solutions with better diversity and convergence. (shrink)

In association with the development of intermittent renewable energy generation, dynamic multiobjective dispatch faces more challenges for power system operation due to significant REG uncertainty. To tackle the problems, a day-ahead, optimal dispatch problem incorporating energy storage is formulated and solved based on a robust multiobjective optimization method. In the proposed model, dynamic multistage ES and generator dispatch patterns are optimized to reduce the cost and emissions. Specifically, strong constraints of the charging/discharging behaviors of the ES in the space-time (...) domain are considered to prolong its lifetime. Additionally, an adaptive robust model based on minimax multiobjective optimization is formulated to find optimal dispatch solutions adapted to uncertain REG changes. Moreover, an effective optimization algorithm, namely, the hybrid multiobjective Particle Swarm Optimization and Teaching Learning Based Optimization, is employed to seek an optimal Pareto front of the proposed dispatch model. This approach has been tested on power system integrated with wind power and ES. Numerical results reveal that the robust multiobjective dispatch model successfully meets the demands of obtaining solutions when wind power uncertainty is considered. Meanwhile, the comparison results demonstrate the competitive performance of the PSO-TLBO method in solving the proposed dispatch problems. (shrink)

Electric-mechanical equipment manufacturing industries focus on the implementation of intelligent manufacturing systems in order to enhance customer services for highly customized machines with high-profit margins such as electric power transformers. Intelligent manufacturing consists in using supply chain data that are integrated for smart decision making during the production life cycle. This research, in cooperation with a large electric power transformer manufacturer, provides an overview of critical intelligent manufacturing technologies. An ontology schema forms the terminology relationships needed to build two intelligent (...) supply chain management modules for the IM system demonstration. The two core modules proposed in this research are the intelligent supplier selection and component ordering module and the product quality prediction module. The intelligent supplier selection and component ordering module dispatches orders that match the best options of suppliers based on combined analytic hierarchy process analysis and multiobjective integer optimization. In the case study, the intelligent supplier selection and component ordering module demonstrates several acceptable Pareto solutions based on strict constraints, which is a very challenging task for decision makers without assistance. The second module is the product quality prediction module which uses multivariate regression and ARIMA to predict the quality of the finished products. Results show that the R square values are very close to 1. The module shortens the time for the company to accurately judge whether the two semifinished iron cores for the product meet the quality requirements. The component supplier selection module and the finished product quality prediction module developed in this research can be extended to other IM systems for general high-end equipment manufacturers using mass customization. (shrink)

In multiple robot systems, the problem of allocation of complex tasks to heterogeneous teams of robots, also known as the multiple robot coalition formation problem, has begun to receive considerable attention. Efforts to address the problem range from heuristics based approaches that search the subspaces of the coalition structure to evolutionary learning approaches. Conventional approaches typically strive to optimize a single objective function such as the number of tasks executed or the time required to execute all tasks, or a weighted (...) function of such objectives. In real world applications, objectives such as minimizing distance traveled and maximizing the number of tasks completed are often conflicting in nature. The coalition formation problem thus naturally lends itself to a multi-objective optimization approach based on evolutionary learning. In this paper, we formulate the problem of mapping coalitions of robots to a set of tasks as a multi-objective optimization problem and propose a variant of non-dominated sorting genetic algorithm to arrive at trade-off solutions. Additionally, we extend the solution to domains where robot resources are non-additive. Simulations demonstrate the efficacy of the proposed approach in generating the set of Pareto-optimal solutions. (shrink)

Designing a mechanism that provides a direct incentive for an individual to report her utility function over several alternatives is a difficult task. A framework for such mechanism design is the following: an individual (a decision maker) is faced with an optimization problem (e.g., maximization of expected utility), and a mechanism designer observes the decision maker’s action. The mechanism does reveal the individual’s utility truthfully if the mechanism designer, having observed the decision maker’s action, infers the decision maker’s utilities (...) over several alternatives. This paper studies an example of such a mechanism and discusses its application to the problem of optimal social choice. Under certain simplifying assumptions about individuals’ utility functions and about how voters choose their voting strategies, this mechanism selects the alternative that maximizes Harsanyi’s social utility function and is Pareto-efficient. (shrink)

A compromise is an agreement that involves mutual concessions. Each party gets less than it feels entitled to, but agrees to it because the situation it anticipates under the deal is better than the one it expects in the absence of a deal: conflict, exit or arbitration by a third party. Some compromises, however, are bad, and others are good. This article discusses three conjectures about what it is that makes a compromise good. Is a good compromise an honourable compromise, (...) one that enables each party to save face? Is it rather a fair compromise, one that contributes to the progress of justice independently defined? Or is it a Pareto-improving compromise, one that changes things in such a way that it ends up making everyone better off than under the status quo? A compromise is never as good as a consensus, but it is generally better than nothing, and often achievable when a consensus is not. And when it is, trying to make it as good as possible in each of the three ways described is always worthwhile. © 2012 Government and Opposition Ltd. (shrink)

William Dembski (No free lunch: why specified complexity cannot be purchased without intelligence, 2002) claimed that the NFL theorems from optimization theory render darwinian biological evolution impossible. Häggström (Biology and Philosophy 22:217–230, 2007) argued that the NFL theorems are not relevant for biological evolution at all, since the assumptions of the NFL theorems are not met. Although I agree with Häggström (Biology and Philosophy 22:217–230, 2007), in this article I argue that the NFL theorems should be interpreted as dealing (...) with an extreme case within a much broader context. This broader context is in fact relevant for scientific research of certain evolutionary processes; not in the sense that the theorems can be used to draw conclusions about any intelligent design inference, but in the sense that it helps us to interpret computer simulations of evolutionary processes. As a result of this discussion, I will argue that from simulations, we do not learn much about how complexity arises in the universe. This position is in contrast with certain claims in the literature that I will discuss. (shrink)

Virtual bargaining theory suggests that social agents aim to resolve non-cooperative games by identifying the strategy profile which they would agree to play if they could openly bargain. The theory thus offers an explanation of how social agents resolve games with multiple Nash equilibria. One of the main questions pertaining to this theory is how the principles of the bargaining theory could be applied in the analysis of hypothetical bargaining in non-cooperative games. I propose a bargaining model based on the (...) benefit-equilibrating bargaining solution concept for non-cooperative games, broadly in line with the principles underlying Conley and Wilkie's ordinal egalitarian solution for Pareto optimal point selection problems with finite choice sets. I provide formal characterizations of the ordinal and the cardinal versions of BES, discuss their application to n-player games, and compare model's theoretical predictions with the data available from several experiments involving `pie games'. (shrink)

In this paper I explore a positivist methodological tradition in early demand theory, as exemplified by several common traits that I draw from the works of V. Pareto, H. L. Moore and H. Schultz. Assuming a current approach to explanation in the social sciences, I will discuss the building of their various explanans, showing that the three authors agreed on two distinctive methodological features: the exclusion of any causal commitment to psychology when explaining individual choice and the mandate (...) to test the truth of demand theory on aggregate data by statistical means. However, I also contend, from an epistemological point of view, that the truth of demand theory was conceived of in three different ways by our authors. Inspired by Poincaré, Pareto assumed that many different theories could account for the same data on individual choice, coming close to a kind of conventionalism -though I prefer to refer to this position as theoreticism. Moore was himself akin to Pearson's approach, which could be named descriptivist insofar as it resolved scientific laws into statistical descriptions of the data. Finally, Schultz tried to reconcile both approaches in an adequationist stance with no success, as we shall see. (shrink)

Two agents endowed with different categorisations engage in bargaining to reach an understanding and agree on a common categorisation. We model the process as a simple non-cooperative game and demonstrate three results. When the initial disagreement is focused, the bargaining process has a zero-sum structure. When the disagreement is widespread, the zero-sum structure disappears and the unique equilibrium requires a retraction of consensus: two agents who individually associate a region with the same category end up rebranding it under a different (...) category. Finally, we show that this last equilibrium outcome is Pareto dominated by a cooperative solution that avoids retraction; that is, the unique equilibrium agreement may be inefficient. (shrink)

In this paper I investigate the possibility of a dictatorship in the context of Harsanyi's Social Aggregation Theorem. Preliminarily, some propositions about Harsanyi's Theorem are presented using an alternative principle that I name Quasi-strong Pareto, which is the latter part of Strong Pareto. Then I define dictatorship as a requirement that social preference agrees with a dictator's preference or those of members of dictatorial group even if their preferences strictly contradict those of all other people in the society. (...) Conclusively, although in each version of Harsanyi's Theorem with Pareto Indifference, Weak Preference Pareto or Weak Pareto the social utility function may have a form of dictatorship, however if individuals' vNM utility functions are all 'individualistic' and Quasi-strong Pareto is satisfied, then the dictatorship is excluded. (shrink)

Amartya Sen has demonstrated a possible inconsistency between a (liberal) right and Pareto optimality. Neither Sen nor the subsequent literature have discussed the origin of the rights that lead to the liberal paradox. In this article I examine one possible origin of rights definitions-a constitutional contract agreed to by all members of the community. Constitutional rights are show to be vulnerable to a similar paradox as with liberal rights, but if the writers of the constitution were correct in (...) their choice of actions to protect, such paradoxes will be unlikely and involve small welfare losses when they do occur. The article demonstrates that both the origin of rights and their potential role in advancing the interests of citizens can be explained using a utilitarian/welfarist methodology. (shrink)

In the 1950s, Chomsky and his colleagues began attempts to reduce the complexity of natural language phonology and syntax to a few general principles. It wasn’t long before philosophers, notably John Searle and H. Paul Grice, started looking for ways to do the same for rational communication (Chapman 2005). In his 1967 William James Lectures, Grice presented a loose optimization system based on his maxims of conversation. The resulting papers (especially Grice 1975) strike a fruitful balance between intuitive exploration (...) and formal development. Though the work is not particularly formal, it marks the birth of modern formal pragmatics. Pragmatics is central to the theory of linguistic meaning because, to paraphrase Levinson (2000), the encoded content of the sentences we utter is only the barest sketch of what we actually communicate with those utterances. Utterance interpretation involves complex interactions among (i) semantic content, (ii) the context of utterance, and (iii) general pragmatic pressures (of which Grice’s maxims are one conception). The starting point for a formal pragmatics is the observation that speakers agree to a remarkable extent on the interpretations of the utterances they hear, suggesting that there are deep regularities across speakers, utterance contexts, and sentence types in how (i)–(iii) interact. An overarching challenge for pragmatic theory is that semantic content and the context of utterance influence each other. It is common, for instance, to find that the meaning of a sentence is crucially incomplete without contextual information. Indexicals and demonstratives are paradigm cases: ‘I am here now’ doesn’t have a fully specified denotation without information about who the speaker is, when he is speaking, and where he is speaking. Similarly, modal auxiliaries like must admit of a wide range of interpretations.. (shrink)

G. A. Cohen's Rescuing Justice and Equality proposes that both concepts need rescuing from the work of John Rawls. Especially, it is concerned with Rawls' famous second principle of justice according to which social primary goods should be distributed equally unless an unequal distribution is to the benefit of the worst off. The question is why this would ever be necessary if all parties are just. Cohen and I agree that Rawls cannot really justify inequalities on the basis given. But (...) he also thinks equality is the correct analysis of justice, though he provides no actual direct arguments for this. He does, however, provide a striking analytical argument claiming that fundamental principles of justice must be fact insensitive, and that Rawls's view of justice violates this requirement. I argue that the requirement is itself misconceived and that principles of justice cannot possibly be fact insensitive in the sense developed by Cohen. Few philosophers share this view of Cohen's—which I argue is due to several conceptual mistakes. With these ironed out, the contractarian view, broadly speaking, is seen to be plausible and powerful. Meanwhile Cohen appears to embrace intuitionism, a stance that cannot possibly be acceptable in social philosophy. In the end, Cohen is successful in arguing that Rawls cannot have what he wants, but neither is Cohen successful in claiming that justice is equality. (shrink)

Learning equivalence classes of acyclic models with latent and selection variables from multiple datasets with overlapping variables is discussed. The problem of inferring the presence of latent variables, their relation to the observables, and the relation among themselves, is considered. A different approach for identifying causal structures, one that results in much simpler equivalence classes, is provided. It is found that the computational cost is much higher than the procedure implemented, but if datasets are individually of modest dimensionality, it might (...) be doable in practice. From the point of view of search algorithms for optimizing structure, much of the machinery of combinatorial optimization could optimize the penalized composite likelihood score by enforcing constraints such that the independence models over different subsets of variables agree on the overlapping sets. (shrink)

Using the economic concepts of rational self-interest, pareto-optimality, [[sic]] public goods, public capital and investment, and contracts, this book attempts to explain and justify the origins of rights and property, and to analyze some of the problems and failures of the U.S. political system. Eschewing a political theory based upon a "true" or "correct" theory of justice, Buchanan claims that political institutions should satisfy people’s actual wants. In particular, he claims that political rights and distributions of private and public (...) goods should be those that free persons in a state of nature would agree to and contract into, given complete information about themselves and their relationships. Once these rights have been agreed upon, then political institutions must protect this contractual agreement and provide public goods that persons want. (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:A New Stoicism by Lawrence C. BeckerEric BrownLawrence C. Becker. A New Stoicism. Princeton: Princeton University Press, 1998. Pp. vii + 216. Cloth, $ 29.95.As the title suggests, A New Stoicism is not primarily a work in the history of philosophy but an appropriation for current purposes. Becker boldly identifies himself as a stoic (sic) and seeks to “outline a contemporary version of stoic ethics” (6). While disdaining (...) much of the ancients’ provocative rhetoric, Becker defends some of the most controversial Stoic positions, including apatheia and what he calls “the Axiom of Futility.” Indeed, he apostasizes significantly only by surrendering teleology.Historical inquiry is limited to commentaries that are appended to each chapter in order to show “in detail how this work can justify calling itself stoic” (7). Here Becker offers summaries of and references for central interpretive disputes, generally appends his own views, and occasionally argues for them. These commentaries typically shed more light on Becker’s project than on the ancients, but they do suffice to justify calling the project Stoic. And historically minded readers will still find much of value in this book, especially by reflecting on Becker’s appropriations and appreciations.As a contribution to contemporary ethics, Becker’s program—“neither a comprehensive ethical theory nor a practical handbook” (7)—aims to follow the facts, especially of moral psychology. To Becker “every norm (as a fact about the world) is internal to some, agent’s project” (77).1 To show how humans have not just a hodge-podge of [End Page 162] personal norms both nasty and nice but a set of recognizably moral norms, Becker counts on certain “schematic and probabilistic” (12) facts about human nature and natural psychological development, including the attribution of a “built-in motivational pressure for reducing cognitive dissonance—for achieving logical consistency and connectedness (integration) among the objects of thought” (87). On Becker’s account, a human being naturally reflects on the norms generated by her various endeavors, and her reflection leads her eventually to the conclusion that “I am required, as a necessary condition of exercising my agency, to take solely the perfection of (the exercise of) my agency based on practical reasoning all-things-considered as my most comprehensive and controlling endeavor” (116–117). The naturally perfect agent recognizes the norms generated by this most controlling endeavor as axiomatically superordinate to all her other norms (42) and achieves maximal integration (and maximal versatility!) of her possible endeavors, but Becker takes pains to insist that she will still experience conflict, passion, and her own idiosyncratic pleasures and pains.Becker’s achievement is considerable. He puts to rest the caricature of the impassively passive stoic and challenges modern moral philosophy to take fuller account of real and diverse moral psychology, and in doing so he provides clear evidence for thinking that philosophy benefits by a close engagement with its Stoic past.But Becker’s project faces some difficult questions. Those unsympathetic to the immediate move from facts about endeavors to norms, for example, will press “the normative question.” I wish he had said more about how social virtue enters. Consider Harry, a remarkably well-integrated agent who has not integrated any norms to help people outside of his limited community (see esp. 97). Can Becker say that Harry is wrong, as the ancient Stoics would? Some of the ancients seem to give an account of social development that naturally culminates in positive concern for all human beings, but Becker pulls up well short of this in his brief remarks about social development (74–76, 96–97, 156). Other ancients seem to argue that naturally perfected agency agrees with the divine order of the cosmos, which recognizes no relevant distinctions between various communities, but Becker has jettisoned this sort of argument. Perhaps Becker will say that Harry can have healthy integration but cannot have the versatility required of ideal agency (103–107) since ideal agency requires “the optimization of the agent’s practically possible endeavors” (107) and engagement with outsiders is a practical possibility. But Becker’s notions of an endeavor and of practical possibility themselves raise difficult questions surrounding intention.Stylistically, Becker’s initially charming use... (shrink)

In lieu of an abstract, here is a brief excerpt of the content:Reviewed by:Health Care Ethics: Theological Foundations, Contemporary Issues, and Controversial Cases, revised edition by Michael R. Panicola, David M. Belde, John Paul Slosar, and Mark F. Repenshek, and: On Moral Medicine: Theological Perspectives in Medical Ethics, third edition ed. by M. Therese Lysaught and Joseph J. Kotva Jr. with Stephen E. Lammers and Allen VerheyLindsey EsbensenReview of Health Care Ethics: Theological Foundations, Contemporary Issues, and Controversial Cases, revised edition (...) MICHAEL R. PANICOLA, DAVID M. BELDE, JOHN PAUL SLOSAR, AND MARK F. REPENSHEK Winona, MN: Anselm Academic, 2011. 438 pp. $37.95Review of On Moral Medicine: Theological Perspectives in Medical Ethics, third edition EDITED BY M. THERESE LYSAUGHT AND JOSEPH J. KOTVA JR. WITH STEPHEN E. LAMMERS AND ALLEN VERHEY Grand Rapids, MI: Eerdmans, 2012. 1180 pp. $61.55Health Care Ethics and On Moral Medicine are excellent resources for those studying and teaching in the field of medical ethics. Each text on its own provides a very good initial evaluation of contemporary conversations in health care ethics. Together they provide a thorough foundation for the study of health care ethics that encourages further exploration of topics in the field. They both provide an excellent overview for undergraduate students as well as anyone interested in the field of medical morality.Health Care Ethics is especially helpful for those entering the field of ethics in general and the more particular realm of medical morality. User-friendly, [End Page 211] the book is accessible to beginners while also being relevant to those already well-versed in medical ethics. The book provides case studies culled from the experiences of the authors throughout their careers in the practice of medical ethics. Perhaps even more useful, however, are the other exercises in which readers are given the opportunity to actively engage the text in order to discover and more fully articulate their own moral stance. Although Health Care Ethics approaches the topic from a theological perspective, using scriptural passages as well as broader religious themes and contexts, the book is accessible to those outside of the religious arena as well.The first three chapters lay the framework for general theological and ethical inquiry while the later chapters discuss more specific topics in applied health care ethics. The opening chapters by Michael Panicola are thought-provoking, especially since they encourage readers to participate in exercises to determine how they would respond to particular scenarios in their personal decision making. For example, after laying out the classic ethical theories, readers are asked to take a “quiz” by responding to multiple-choice questions to determine how they would respond to various ethical situations. The exercise demonstrates that moral discernment that relies on one ethical theory alone or one single approach to ethics is too narrow and confining for authentic dialogue in ethics. Another exercise calls upon readers to examine their fundamental bases for personal decision making by asking them to create a list of what they think are the ten things that constitute human flourishing and then narrow that list down to the top two. In addition to being engaging, these exercises help readers establish their personal moral stance by asking them to appropriate foundational norms in the process of moral discernment to the case studies throughout the book. They also help readers apply these norms to the specific topics in health care ethics presented in the later chapters.The authors of Health Care Ethics clearly identify human flourishing as the center and goal for all ethical inquiry. Demonstrating that “human flourishing” has different connotations for different people, they also argue that certain norms can be agreed upon to establish a framework for all conversations regarding moral decision making in health care. They especially emphasize a concern for the optimization of human flourishing in final chapters of the text. Chapters 4–12 provide detailed examinations of current topics in medical ethics. Each chapter includes case studies that raise questions concerning social ethics as well as health care morality, employing sources from law, sociology, philosophy, and theology. Each case underscores the complexity of moral decision making in health care ethics as well as the point that there is no one, pure approach to medical ethics that... (shrink)

It is possible that the world contains infinitely many agents that have positive and negative levels of well-being. Theories have been developed to ethically rank such worlds based on the well-being levels of the agents in those worlds or other qualitative properties of the worlds in question, such as the distribution of agents across spacetime. In this thesis I argue that such ethical rankings ought to be consistent with the Pareto principle, which says that if two worlds contain the (...) same agents and some agents are better off in the first world than they are in the second and no agents are worse off than they are in the second, then the first world is better than the second. I show that if we accept four axioms – the Pareto principle, transitivity, an axiom stating that populations of worlds can be permuted, and the claim that if the ‘at least as good as’ relation holds between two worlds then it holds between qualitative duplicates of this world pair – then we must conclude that there is ubiquitous incomparability between infinite worlds. I show that this is true even if the populations of infinite worlds are disjoint or overlapping, and that we cannot use any qualitative properties of world pairs to rank these worlds. Finally, I argue that this incomparability result generates puzzles for both consequentialist and non-consequentialist theories of objective and subjective permissibility. (shrink)

Pareto principles are at the core of ethics and decision theory. The Strong Pareto principle says that if one thing is better than another for someone and at least as good for everyone else, then the one is overall better than the other. But a host of famous figures express it differently, with ‘not worse’ in place of ‘at least as good.’ In the presence of parity (or incommensurability), this results in a strictly stronger Pareto principle, which (...) I call Super‐Strong Pareto. Super‐Strong Pareto, however, yields cyclic betterness and is therefore false. I point out a number of influential arguments—concerning population ethics, collective action problems, and decision‐making in the face of parity and uncertainty—that crucially rely on Super‐Strong Pareto and are therefore unsound. I then turn to the most influential argument against the possibility of parity—Broome's collapsing argument—and argue that it likewise relies on Super‐Strong Pareto reasoning and is therefore question‐begging. Finally, I turn to the much‐neglected question of how to justify Strong Pareto. The answer I arrive at, which emphasizes tie‐breaking, yields a striking insight, namely that Super‐Strong Pareto amounts to the denial of insensitivity to mild sweetening. That is what makes it problematic in the presence of parity. (shrink)

Optimization is about finding the best available object with respect to an objective function. Mathematics and quantitative sciences have been highly successful in formulating problems as optimization problems, and constructing clever processes that find optimal objects from sets of objects. As computers have become readily available to most people, optimization and optimized processes play a very broad role in societies. It is not obvious, however, that the optimization processes that work for mathematics and abstract objects should (...) be readily applied to complex and open social systems. In this paper we set forth a framework to understand when optimization is limited, particularly for complex and open social systems. (shrink)

A two-stage sequential choice model is studied, the first stage being defined by q-Pareto multicriterial choice rule, and the second stage being defined by scalar extremization model. In this model, at the first stage the q-Pareto rule choses alternatives which are not only undominated in terms of Pareto comparison, but also includes into choice the alternatives which are dominated by no more than q alternatives. Since the choice set of the first-stage usually contains too many elements, obtained (...) set is used as a presentation for the second stage constructed by a scalar extremization model. The properties of the model are studied as well as its representability to one-stage scalar extremization model. (shrink)

The relations between rationality and optimization have been widely discussed in the wake of Herbert Simon's work, with the common conclusion that the rationality concept does not imply the optimization principle. The paper is partly concerned with adding evidence for this view, but its main, more challenging objective is to question the converse implication from optimization to rationality, which is accepted even by bounded rationality theorists. We discuss three topics in succession: (1) rationally defensible cyclical choices, (2) (...) the revealed preference theory of optimization, and (3) the infinite regress of optimization. We conclude that (1) and (2) provide evidence only for the weak thesis that rationality does not imply optimization. But (3) is seen to deliver a significant argument for the strong thesis that optimization does not imply rationality. (shrink)

Mental representations have continuous as well as discrete, combinatorial properties. For example, while predominantly discrete, phonological representations also vary continuously; this is reflected by gradient effects in instrumental studies of speech production. Can an integrated theoretical framework address both aspects of structure? The framework we introduce here, Gradient Symbol Processing, characterizes the emergence of grammatical macrostructure from the Parallel Distributed Processing microstructure (McClelland, Rumelhart, & The PDP Research Group, 1986) of language processing. The mental representations that emerge, Distributed Symbol Systems, (...) have both combinatorial and gradient structure. They are processed through Subsymbolic Optimization–Quantization, in which an optimization process favoring representations that satisfy well-formedness constraints operates in parallel with a distributed quantization process favoring discrete symbolic structures. We apply a particular instantiation of this framework, λ-Diffusion Theory, to phonological production. Simulations of the resulting model suggest that Gradient Symbol Processing offers a way to unify accounts of grammatical competence with both discrete and continuous patterns in language performance. (shrink)

One of the more obscure arguments for Rawls’ difference principle dubbed ‘the Pareto argument for inequality’ has been criticised by G. A. Cohen (1995, 2008) as being inconsistent. In this paper, we examine and clarify the Pareto argument in detail and argue (1) that justification for the Pareto principles derives from rational selfinterest and thus the Pareto principles ought to be understood as conditions of individual rationality, (2) that the Pareto argument is not inconsistent, contra (...) Cohen, and (3) that the kind of bargaining model required to arrive at the particular unequal distribution that the difference principle picks out is a model that is not based on bargaining according to one’s threat advantage. (shrink)