We reopen the investigation into the formal and conceptual relationship between bidirectional optimality theory (Blutner in J Semant 15(2):115–162, 1998 , J Semant 17(3):189–216, 2000 ) and game theory. Unlike a likeminded previous endeavor by Dekker and van Rooij (J Semant 17:217–242, 2000 ), we consider signaling games not strategic games, and seek to ground bidirectional optimization once in a model of rational step-by-step reasoning and once in a model of reinforcement learning. We give sufficient conditions for (...) equivalence of bidirectional optimality and the former, and show based on numerical simulations that bidirectional optimization may be thought of as a process of reinforcement learning with lateral inhibition. (shrink)

In this paper, we study solution concepts for cooperative games with stochastic payoffs. we define four kinds of solution concepts, namely the most coalitional (marginal) stable solution and the fairest coalitional (marginal) solution, by minimizing the total variance of excesses of coalitions (individual players). All these four concepts are optimal solutions of corresponding optimal problem under the least square criterion. It turns out that the fairest coalitional (marginal) solution belongs to the set of the most coalitional (marginal) stable solutions. (...) Inspired by the definition of nucleolus, we propose various extended nucleolus based on lexicographic criterion. Furthermore, axiomatizations of the proposed solutions are exhibited through the linkage between the stochastic and deterministic models. (shrink)

In this paper, we study the structural optimization of community governance in smart cities and optimize the structure based on the game analysis of dynamic planning evolution. Theoretically, the connotation and extension of the concept of “self-organization” are cleared, and the environment and conditions of community self-organization formation, the formation process of community self-organization, and the types of community self-organization are discussed. The so-called “self-organization” is a process of spontaneously moving from disorder to order, and the environment and conditions (...) of community self-organization are mainly the openness, nonequilibrium state, and nonlinearity of the system. The key parameters of the contract with the change of the values of each factor make up for the inability to collect data for the empirical study in this paper; then, it presents four linear stages along with the cause such as self-creation, self-expansion, self-maintenance, and self-degeneration, respectively. The types of community self-organization mainly include community self-organization with random aggregation, socialized community self-organization, and stable community self-organization with autonomy orientation. By systematically sorting out the relationship between community self-organization and government, while confirming the positive significance of community self-organization to community cultural governance, various complex conflicts and game relationships will deeply affect the actual effectiveness of cultural governance and provide useful knowledge reference for future community cultural governance. (shrink)

§ 1. Introduction. Perhaps the most surprising recent development in complexity theory is the discovery that the class NP can be characterized using a form of randomized proof checker that only examines a constant number of bits of the “proof” that a string is in a language [6, 5, 31, 3, 4]. More specifically, writing ∣x∣ for the length of a string x, a language L in the class NP of languages recognizable in Nondeterministic polynomial time is traditionally given by (...) a polynomial p and a polynomial-time predicate P such that a string x is in L iff there is some string y satisfying P, where ∣y∣ ≤ p. Intuitively, we can think of a string y as a possible proof that x ϵ L, with the predicate P some kind of proof checker that distinguishes good proofs from bad ones. A string x is therefore in a language L ϵ NP if there is a short proof that x ϵ L, and not in L otherwise. The surprising discovery is that the deterministic proof checker that reads the entire input and proof can be replaced by a probabilistic verifier that on input x and possible proof y, where y is presented in a certain way, flips at most O coins and reads at most a constant number of bits of x and y. Obviously, a probabilistic verifier that does not read the whole proof will sometimes make mistakes. However, the surprising and essentially non-intuitive mathematical fact is that for each language L in NP, it is possible to find a polynomial q and verifier V flipping a logarithmic number of coins and reading a constant number of bits such that, for any x ϵ L, there exists y with ∣y∣ ≤ q and with V accepting with probability 1 and, for x ∉ L, there is no y with ∣y∣ ≤ q and with V accepting with probability ≥ 1/4. This idea canalsobeextended to PSPACE [10, 9], using a game that alternates between two players instead of a proof presented by a “single player.”. (shrink)

Games and Decision Making, Second Edition, is a unique blend of decision theory and game theory. From classical optimization to modern game theory, authors Charalambos D. Aliprantis and Subir K. Chakrabarti show the importance of mathematical knowledge in understanding and analyzing issues in decision making. Through an imaginative selection of topics, Aliprantis and Chakrabarti treat decision and game theory as part of one body of knowledge. They move from problems involving the individual decision-maker to progressively more complex problems (...) such as sequential rationality, auctions, and bargaining. By building each chapter on material presented earlier, the authors offer a self-contained and comprehensive treatment of these topics. Successfully class-tested in an advanced undergraduate course at the Krannert School of Management and in a graduate course in economics at Indiana University, Games and Decision Making, Second Edition, is an essential text for advanced undergraduates and graduate students of decision theory and game theory. The book is accessible to students who have a good basic understanding of elementary calculus and probability theory. (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)

The conventional community sports facility allocation methods have high minimum costs, and a new community sports facility allocation performance optimization method is designed based on a linear programming model in order to reduce the performance capital investment. The standardized community sports facility allocation performance objective function is established, and a pairwise model is built to divide the feasible and optimal solutions, and the feasible solutions and their constraints are found out. Establish a community sports facility configuration performance optimization (...) model, delineate the boundaries of the optimal solution by bifurcation, and set the feasible domain of the performance optimization model. The performance optimization algorithm is designed to improve the speed of community sports facility allocation performance optimization. In the experiment, the method is compared with data-driven method, digital management method, and evolutionary game algorithm, which requires less capital investment in spring, autumn, and winter than digital management method and evolutionary game algorithm, and the minimum capital investment in summer is less than the other three methods. From the above experimental data, it is clear that the performance optimization method has the smallest minimum capital investment and achieves the purpose of reducing the input cost. (shrink)

Major events such as the COVID-19 pandemic, Olympic Games, and G20 Summit bring about supplier disruption risks and challenges to supply chain management. To help deal with these risks, a virtual dual-sourcing production-inventory system can be deployed. In this paper, we study such a system which consists of a raw material supplier, a manufacturer, and a virtual dual-sourcing contingency supplier. The manufacturer needs to determine the production, procurement, and inventory plan of raw materials. When its supplier is interrupted, the (...) manufacturer may need to adjust the production and inventory plan and work with the contingency supplier. We develop a system dynamics method to simulate the operations in this production-inventory system to identify the approximately optimal order-up-to-level inventory policies. We find that the virtual dual production-inventory strategy can be the optimal contingency policy to deal with supplier dynamic disruption risks. Furthermore, for disruption risk with low frequency and long duration, the manufacturer should increase the safety inventory level before the disruption. Otherwise, it should increase the safety inventory level in every cycle. (shrink)

Maynard Smith’s defenses of adaptationism and of the value of optimization theory in evolutionary biology are both criticized. His defense does not adequately respond to the criticism of adaptationism by Gould and Lewontin. It is also argued here that natural selection cannot be interpreted as an optimization process if the objective function to be optimized is either (i) interpretable as a fitness, or (ii) correlated with the mean population fitness. This result holds even if fitnesses are frequency-independent; the (...) problem is further exacerbated in the frequency-dependent context modeled by evolutionary game theory. However, Eshel and Feldman’s new results on “long-term” evolution may provide some hope for the continuing relevance of the game-theoretic framework. These arguments also demonstrate the irrelevance of attempts by Intelligent Design creationists to use computational limits on optimization algorithms as evidence against evolutionary theory. It is pointed out that adaptation, natural selection, and optimization are not equivalent processes in the context of biological evolution. (shrink)

Individual-as-maximizing agent analogies result in a simple understanding of the functioning of the biological world. Identifying the conditions under which individuals can be regarded as fitness maximizing agents is thus of considerable interest to biologists. Here, we compare different concepts of fitness maximization, and discuss within a single framework the relationship between Hamilton’s (J Theor Biol 7:1–16, 1964) model of social interactions, Grafen’s (J Evol Biol 20:1243–1254, 2007a) formal Darwinism project, and the idea of evolutionary stable strategies. We distinguish cases (...) where phenotypic effects are additive separable or not, the latter not being covered by Grafen’s analysis. In both cases it is possible to define a maximand, in the form of an objective function ϕ(z), whose argument is the phenotype of an individual and whose derivative is proportional to Hamilton’s inclusive fitness effect. However, this maximand can be identified with the expression for fecundity or fitness only in the case of additive separable phenotypic effects, making individual-as-maximizing agent analogies unattractive (although formally correct) under general situations of social interactions. We also feel that there is an inconsistency in Grafen’s characterization of the solution of his maximization program by use of inclusive fitness arguments. His results are in conflict with those on evolutionary stable strategies obtained by applying inclusive fitness theory, and can be repaired only by changing the definition of the problem. (shrink)

SummaryThe problems of operations research, optimized at the tactical and strategic level, have a domain of interest much broader than many of its earlier suboptimization problems. Its appeal to scientific method requires the construction of a model from which predictions can be made. This model must have the comprehensive character of those proposed by philosophy and the sciences. Such a model is available in the form of war gaming, a traditional military training vehicle transformed in such a way as to (...) make it a research tool of great power and flexibility and which can assume a multitude of forms. The war game as a new research tool, when applied to the important problems at a high level of optimization, carries with it the excitement of a pioneering venture and the promise of contributions of greatly increased importance to the development of military science. (shrink)

The main purpose of this article is to introduce the weighted ENSC value for cooperative transferable utility games which takes into account players’ selfishness about the payoff allocations. Similar to Shapley’s idea of a one-by-one formation of the grand coalition [Shapley ], we first provide a procedural implementation of the weighted ENSC value depending on players’ selfishness as well as their marginal contributions to the grand coalition. Second, in the spirit of the nucleolus [Schmeidler ], we prove that the (...) weighted ENSC value is obtained by lexicographically minimizing a complaint vector associated with a new complaint criterion relying on players’ selfishness. (shrink)

_A new theory of how and why we cooperate, drawing from economics, political theory, and philosophy to challenge the conventional wisdom of game theory_ Game theory explains competitive behavior by working from the premise that people are self-interested. People don’t just compete, however; they also cooperate. John Roemer argues that attempts by orthodox game theorists to account for cooperation leave much to be desired. Unlike competing players, cooperating players take those actions that they would like others to take—which Roemer calls (...) “Kantian optimization.” Through rigorous reasoning and modeling, Roemer demonstrates a simpler theory of cooperative behavior than the standard model provides. (shrink)

The future of human computation benefits from examining tasks that agents already perform and designing environments to give those tasks computational significance. We call this natural human computation. We consider the possible future of NHC through the lens of Swarm!, an application under development for Google Glass. Swarm! motivates users to compute the solutions to a class of economic optimization problems by engaging the attention dynamics of crowds. We argue that anticipating and managing economies of attention provides one of (...) the most tantalizing future applications for NHC. (shrink)

Coal mine safety management involves many interested parties and there are complex relationships between them. According to game theory, a multiparty evolutionary game model is established to analyze the selection of strategies. Then, a simplified three-party model is taken as an example to carry out detailed analysis and solution. Based on stability theory of dynamics system and phase diagram analysis, this article studies replicator dynamics of the evolutionary model to make an optimization analysis of the behaviors of those interested (...) parties and the adjustment mechanism of safety management policies and decisions. The results show how the charge of supervision of government department and inspection of coal mine enterprise impact the efficiency of safety management and the effect of constraint measures and incentive and other measures in safety management. (shrink)

The study of complexity and optimization in decision theory involves both partial and complete characterizations of preferences over decision spaces in terms of real-valued monotones. With this motivation, and following the recent introduction of new classes of monotones, like injective monotones or strict monotone multi-utilities, we present the classification of preordered spaces in terms of both the existence and cardinality of real-valued monotones and the cardinality of the quotient space. In particular, we take advantage of a characterization of real-valued (...) monotones in terms of separating families of increasing sets to obtain a more complete classification consisting of classes that are strictly different from each other. As a result, we gain new insight into both complexity and optimization, and clarify their interplay in preordered spaces. (shrink)

The multilinear extension of a cooperative game was introduced by Owen in 1972. In this contribution we study the Lovász extension for cooperative games by using the marginal worth vectors and the dividends. First, we prove a formula for the marginal worth vectors with respect to compatible orderings. Next, we consider the direct market generated by a game. This model of utility function, proposed by Shapley and Shubik in 1969, is the concave biconjugate extension of the game. Then we (...) obtain the following characterization: The utility function of a market game is the Lovász extension of the game if and only if the market game is supermodular. Finally, we present some preliminary problems about the relationship between cooperative games and combinatorial optimization. (shrink)

Specific to the NCSs where sensor signals can be processed centrally, a collaborative design scheme of dynamic game scheduling and advanced control theory was proposed in the present study. Firstly, by using the Jordan standard state space equation of the research object, the three elements of state noncooperative game were built, and the existence and uniqueness of Nash equilibrium solution were verified. In addition, the iterative equation of the scheduling matrix was derived by complying with the designed utility function. Secondly, (...) refer to the number of restricted states the order of sliding mode was determined. And based on it, the corresponding sliding surface was designed. Subsequently, the quadratic optimization theory was adopted to regulate the control value following the implementation of the scheduling strategy to ensure that the control quality was further enhanced in the limited network service. Lastly, a TrueTime simulation example is established to verify the effectiveness of the proposed scheme. (shrink)

In spectrum sharing cognitive radio networks, unauthorized users are allowed to use the spectrum of authorized users to improve spectrum utilization. Due to limited spectrum resources, how to formulate a reasonable spectrum allocation scheme is very important. As a mathematical analysis tool, game theory can solve the problem of resource allocation well. In recent years, it has been applied to the research of resource allocation in spectrum sharing networks by some literatures. In a cellular network consisting of multiple cellular users (...) and full-duplex end-to-end communication users D2D, the self-interference caused by full-duplex communication and the interference caused by the D2D users to the cellular users will significantly reduce system throughput. In order to reduce the interference in the network, this paper introduces a power control algorithm based on Stackelberg game, which sets the cellular users and D2D users as the leaders and followers, respectively. The cellular users and the D2D users compete with each other to minimize the cost, and we propose new utility functions. We build an optimization problem under the outage probability constraint and power constraint and the transmission power of the users is obtained by using the Lagrangian dual decomposition method. The simulation results show that the proposed game algorithm improves network performance compared with other existing schemes. (shrink)

Through a phenomenological study of horse-human relations, this article explores the ways in which, as embodied beings, we live relationally, rather than as separate human identities. Conceptually this challenges oppositional logic and humanist assumptions, but where poststructuralist treatments of these issues tend to remain abstract, this article is concerned with an embodied demonstration of the ways in which we experience a relational or in-between logic in our everyday lives.

We argue that pedagogic authority relies on love, which is misunderstood if seen as a matter of actions and subjects. Love is based not on finite subjects and objects existing in Euclidean space and linear time, but, rather, on the non-finite ontology, space and time of relations. Loving authority is a matter of calling and vocation, arising from the spontaneous and simultaneous call-and-response of a lively relation. We make this argument through a reading of Buber’s I–You relation and Murdoch’ s (...) account of the responsiveness of ascetic discipline. In presenting this analysis, we draw upon a case study from a research project on Australian teachers and students. (shrink)

Prior research suggests brokers do not always act in the best interests of clients, although morally obligated to do so. We empirically investigated this issue focusing on trades executed at best execution price, before and after the introduction of electronic limit-order trading, on the London Stock Exchange. As a result of limit-order trading, the proportion of trades executed at the best execution price for the customer significantly increased. We attribute this to a sustained increase in the liquidity of stocks as (...) a result of limit-order trading, regardless of market capitalisation. We discuss the ethical implications of our findings and conclude that market structures that enhance market competitiveness may help reconcile broker and client interests. (shrink)

This study examined the link between employees’ adult attachment orientations and perceptions of line managers’ interpersonal justice behaviors, and the moderating effect of national culture. Participants from countries categorized as low collectivistic and high collectivistic completed an online survey. Attachment anxiety and avoidance were negatively related to interpersonal justice perceptions. Cultural differences did not moderate the effects of avoidance. However, the relationship between attachment anxiety and interpersonal justice was non-significant in the Southern Asia cultural cluster. Our findings indicate the importance (...) of ‘fit’ between cultural relational values and individual attachment orientations in shaping interpersonal justice perceptions, and highlight the need for more non-western organizational justice research. (shrink)

The mechanisms responsible for the fine tuning of development, where the wildtype phenotype is reproduced with high fidelity, are not well understood. The difficulty in approaching this problem is the identification of mutant phenotypes indicative of a defect in these fine‐tuning control mechanisms. Evolutionary biologists have used asymmetry as a measure of developmental homeostasis. The rationale for this was that, since the same genome controls the development of the left and right sides of a bilaterally symmetrical organism, departures from symmetry (...) can be used to measure genetic or environmental perturbations. This paper examines the relationship between asymmtry and resistance to organophosphorous insecticides in the Australian sheep blowfly, Lucilia cuprina. A resistance gene, Rop‐1, which encodes a carboxylesterase enzyme, also confers a significant increase in asymmetry. Continued exposure of resistant populations to insecticide has selected a dominant suppressor of the asymmetry phenotype. Genetic evidence indicates that the modifier is the L. cuprina Notch homologue. (shrink)

Abstract In this article we develop a relational understanding of sociality, that is, an account of social life that takes relation as primary. This stands in contrast to the common assumption that relations arise when subjects interact, an account that gives logical priority to separation. We will develop this relational understanding through a reading of the work of Martin Buber, a social philosopher primarily interested in dialogue, meeting, relationship, and the irreducibility and incomparability of reality. In particular, the article contrasts (...) Buber’s work with that of poststructuralist theorists who take as their starting point the deconstruction of the Hegelian logic of binary oppositions. Deconstruction understands difference as the excess that undoes the binary, but Buber, we argue, shows how difference derives from the primacy and ontological undefinability of relation. Relational logic does not exclude the logic of separations and oppositions: relation is the primal ground that makes separations possible. Content Type Journal Article Pages 1-13 DOI 10.1007/s11841-011-0278-9 Authors Andrew Metcalfe, School of Social Sciences and International Studies, University of New South Wales, Sydney, NSW 2052, Australia Ann Game, School of Social Sciences and International Studies, University of New South Wales, Sydney, NSW 2052, Australia Journal Sophia Online ISSN 1873-930X Print ISSN 0038-1527. (shrink)

Humans are incapable of acting as utility maximisers. In contrast, the evolutionary process had considerable time and computational power to select optimal heuristics from a set of alternatives. To view evolution as the optimising agent has revolutionised game theory. Gigerenzer and his co-workers can help us understand the circumstances under which evolution and learning achieve optimisation and Nash equilibria.

Optimization models have often been useful in attempting to understand the adaptive significance of behavioral traits. Originally such models were applied to isolated aspects of behavior, such as foraging, mating, or parental behavior. In reality, organisms live in complex, ever-changing environments, and are simultaneously concerned with many behavioral choices and their consequences. This target article describes a dynamic modeling technique that can be used to analyze behavior in a unified way. The technique has been widely used in behavioral studies (...) of insects, fish, birds, mammals, and other organisms. The models use biologically meaningful parameters and variables, and lead to testable predictions. Limitations arise because nature's complexity always exceeds our modeling capacity. (shrink)

Much like the trade and traits of bubbles in financial markets, similar bubbles appear on the science market. When economic bubbles burst, the drop in prices causes the crash of unsustainable investments leading to an investor confidence crisis possibly followed by a financial panic. But when bubbles appear in science, truth and reliability are the first victims. This paper explores how fashions in research funding and research management may turn science into something like a bubble economy.

Some behavioral economists argue that the honoring of social norms can be adequately modeled as the optimization of social utility functions in which the welfare of others appears as an explicit argument. This paper suggests that the large experimental claims made for social utility functions are premature at best, and that social norms are better studied as equilibrium selection devices that evolved for use in games that are seldom studied in economics laboratories.

This book offers a rigorous, concise, and nontechnical introduction to some of the fundamental insights of rational choice theory. It draws on formal theories of microeconomics, decision making, games, and social choice, and on ideas developed in philosophy, psychology, and sociology. Itzhak Gilboa argues that economic theory has provided a set of powerful models and broad insights that have changed the way we think about everyday life. He focuses on basic insights of the rational choice paradigm--the general conceptualization rather (...) than a particular theory--that survive recent critiques of economic theory's various failures. Gilboa explains the main concepts in language accessible to the nonspecialist, offering a nonmathematical guide to some of the main ideas developed in economic theory in the second half of the twentieth century. Chapters cover feasibility and desirability, utility maximization, constrained optimization, expected utility, probability and statistics, aggregation of preferences, games and equilibria, free markets, and rationality and emotions. Online appendixes offer additional material, including a survey of relevant mathematical concepts. (shrink)

In this paper we analyse the conditions for attributing to AI autonomous systems the ontological status of “artificial moral agents”, in the context of the “distributed responsibility” between humans and machines in Machine Ethics (ME). In order to address the fundamental issue in ME of the unavoidable “opacity” of their decisions with ethical/legal relevance, we start from the neuroethical evidence in cognitive science. In humans, the “transparency” and then the “ethical accountability” of their actions as responsible moral agents is not (...) in contradiction with the unavoidable “opacity” (unawareness) of the brain process by which they perform their moral judgements on the right action to execute. In fact, the moral accountability of our actions depends on what is immediately before and after our “moral judgements” on the right action to execute (formally, deontic first order logic (FOL) decisions). I.e., our moral accountability depends on the “ethical constraints” we imposed to our judgement before performing it in an opaque way. Anyway, our moral accountability depends overall on the “ethical assessment” or explicit “moral reasoning” after and over the moral judgement before executing our actions (deontic higher order logic (HOL) assessment). In this way, in the light of the AI “imitation game”, the consistent attribution of the status of ethically accountable artificial moral agents to autonomous AI systems depends on two similar conditions. Firstly, it depends on the presence of “ethical constraints” to be satisfied in their Machine Learning (ML) supervised optimization algorithm during its training phase, to give the system ethical skills (“competences”) in its decisions. Secondly – and definitely—, it depends on the presence in an AI autonomous system of a deontic HOL “ethical reasoner” to perform an automatic, and fully transparent assessment (metalogical deontic valuation) about the decisions taken by the ethically skilled ML algorithm about the right action to execute, before executing it. Finally, we show that the proper deontic FOL and HOL for this class of artificial moral agents is Kripke’s modal relational logic, in its algebraic topological formalization. This is naturally implemented in the dissipative QFT unsupervised deep learning of our brains, based on the “doubling of the degrees of freedom” (DDF), and then in the so-called “deep-belief” artificial neural networks for the statistical data pre-processing. This unsupervised learning procedure is also compliant with the usage of the “maximin fairness principle”, used as a balancing aggregation principle of the statistical variables in Sen’s formal theory of fairness. (shrink)

The two-volume set LNCS 10350 and 10351 constitutes the thoroughly refereed proceedings of the 30th International Conference on Industrial, Engineering and Other Applications of Applied Intelligent Systems, IEA/AIE 2017, held in Arras, France, in June 2017. The 70 revised full papers presented together with 45 short papers and 3 invited talks were carefully reviewed and selected from 180 submissions. They are organized in topical sections: constraints, planning, and optimization; data mining and machine learning; sensors, signal processing, and data fusion; (...) recommender systems; decision support systems; knowledge representation and reasoning; navigation, control, and autonome agents; sentiment analysis and social media; games, computer vision; and animation; uncertainty management; graphical models: from theory to applications; anomaly detection; agronomy and artificial intelligence; applications of argumentation; intelligent systems in healthcare and mhealth for health outcomes; and innovative applications of textual analysis based on AI. (shrink)

Tetris provides a difficult, dynamic task environment within which some people are novices and others, after years of work and practice, become extreme experts. Here we study two core skills; namely, choosing the goal or objective function that will maximize performance and a feature-based analysis of the current game board to determine where to place the currently falling zoid so as to maximize the goal. In Study 1, we build cross-entropy reinforcement learning models to determine whether different goals result in (...) different feature weights. Two of these optimization strategies quickly rise to performance plateaus, whereas two others continue toward higher but more jagged heights. In Study 2, we compare the zoid placement decisions made by our best CERL models with those made by 67 human players. Across 370,131 human game episodes, two CERL models picked the same zoid placements as our lowest scoring human for 43% of the placements and as our three best scoring experts for 65% of the placements. Our findings suggest that people focus on maximizing points, not number of lines cleared or number of levels reached. They also show that goal choice influences the choice of zoid placements for CERLs and suggest that the same is true of humans. Tetris has a repetitive task structure that makes Tetris more tractable and more like a traditional experimental psychology paradigm than many more complex games or tasks. Hence, although complex, Tetris is not overwhelmingly complex and presents a right-sized challenge to cognitive theories, especially those of integrated cognitive systems. (shrink)

Alongside other types of mass atrocities, genocide has received extensive scholarly, policy, and practitioner attention. Missing, however, is the contribution of economists to better understand and prevent such crimes. This edited collection by 41 accomplished scholars examines economic aspects of genocides, other mass atrocities, and their prevention. Chapters include numerous case studies, probing literature reviews, and completely novel work based on extraordinary country-specific datasets. Also included are chapters on the demographic, gendered, and economic class nature of genocide. Replete with research- (...) and policy-relevant findings, new insights are derived from behavioral economics, law and economics, political economy, macroeconomic modeling, microeconomics, development economics, industrial organization, identity economics, and other fields. Analytical approaches include constrained optimization theory, game theory, and sophisticated statistical work in data-mining, econometrics, and forecasting.A foremost finding of the book concerns atrocity architects' purposeful, strategic use of violence, often manipulating nonrational proclivities among ordinary people to sway their participation in mass murder. Relatively understudied in the literature, the book also analyzes the options of victims before, during, and after mass violence. Further, the book shows how well-intended prevention efforts can backfire and increase violence, how wrong post-genocide design can entrench vested interests to reinforce exclusion of vulnerable peoples, and how businesses can become complicit in genocide. In addition to the necessity of healthy opportunities in employment, education, and key sectors in prevention work, the book shows why new genocide prevention laws and institutions must be based on reformulated incentives that consider insights from law and economics, behavioral economics, and collective action economics. (shrink)

Tetris provides a difficult, dynamic task environment within which some people are novices and others, after years of work and practice, become extreme experts. Here we study two core skills; namely, choosing the goal or objective function that will maximize performance and a feature-based analysis of the current game board to determine where to place the currently falling zoid so as to maximize the goal. In Study 1, we build cross-entropy reinforcement learning models to determine whether different goals result in (...) different feature weights. Two of these optimization strategies quickly rise to performance plateaus, whereas two others continue toward higher but more jagged heights. In Study 2, we compare the zoid placement decisions made by our best CERL models with those made by 67 human players. Across 370,131 human game episodes, two CERL models picked the same zoid placements as our lowest scoring human for 43% of the placements and as our three best scoring experts for 65% of the placements. Our findings suggest that people focus on maximizing points, not number of lines cleared or number of levels reached. They also show that goal choice influences the choice of zoid placements for CERLs and suggest that the same is true of humans. Tetris has a repetitive task structure that makes Tetris more tractable and more like a traditional experimental psychology paradigm than many more complex games or tasks. Hence, although complex, Tetris is not overwhelmingly complex and presents a right-sized challenge to cognitive theories, especially those of integrated cognitive systems. (shrink)

A vexing puzzle about vagueness, rationality, and evolution runs, in crude abbreviation, as follows: vague language use is demonstrably suboptimal if the goal is efficient, precise and cooperative information transmission; hence rational deliberation or evolutionary selection should, under this assumed goal, eradicate vagueness from language use. Since vagueness is pervasive and entrenched in all human languages, something has to give. In this paper, we focus on this problem in the context of signaling games. We provide an overview of a (...) number of proposed ways in which vagueness may come into the picture in formal models of rational and evolutionary signaling. Most argue that vague signal use is simply the best we can get, given certain factors. Despite the plausibility of the proposals, we argue that a deeper understanding of the benefits of vagueness needs a more ecological perspective, namely one that goes beyond the local optimization of signaling strategies in a homogeneous population. As an example of one possible way to expand upon our current models, we propose two variants of a novel multi-population dynamic of imprecise imitation where, under certain conditions, populations with vague language use dominate over populations with precise language use. (shrink)

One is the very founding document of oligopoly theory, Cournot’s seminal work of 1838. This is both because the specific model that he presented has been much studied for its ability to generate complex dynamics and also because of its more general foreshadowing of game theory. It has often been noted that the Cournot equilibrium is but a special case of the Nash (1951) equilibrium, the more general formulation used by modern industrial organization economists in studying oligopoly theory. Indeed, it (...) is sometimes even called the Cournot-Nash equilibrium. Although many of the models of complex oligopoly dynamics use the specific Cournot model, many use more general game theoretic formulations. We note simply as an aside here that Cournot’s work was the first to apply calculus to solving an economic optimization problem and also was the first to introduce supply and demand curves, albeit in the "Walrasian" form with price on the horizontal axis. (shrink)

A major concern of public health authorities is to also encourage adults to be exposed to enriched environments during the pandemic lockdown, as was recently the case worldwide during the COVID-19 outbreak. Games for adults that require physical activity, known as exergames, offer opportunities here. In particular, the output of the gaming industry nowadays offers computer games with extended reality which combines real and virtual environments and refers to human-machine interactions generated by computers and wearable technologies. For example, (...) playing the game in front of a computer screen while standing or walking on a force plate or treadmill allows the user to react to certain infrastructural changes and obstacles within the virtual environment. Recent developments, optimization, and minimizations in wearable technology have produced wireless headsets and sensors that allow for unrestricted whole-body movement. This makes the virtual experience more immersive and provides the opportunity for greater engagement than traditional exercise. Currently, XR serves as an umbrella term for current immersive technologies as well as future realities that enhance the experience with features that produce new controllable environments. Overall, these technology-enhanced exergames challenge the adult user and modify the experience by increasing sensory stimulation and creating an environment where virtual and real elements interact. As a therapy, exergames can potentially create new environments and visualizations that may be more ecologically valid and thus simulate real activities of daily living that can be trained. Furthermore, by adding telemedicine features to the exergame, progress over time can be closely monitored and feedback provided, offering future opportunities for cognitive-motor assessment. To more optimally serve and challenge adults both physically and cognitively over time in future lockdowns, there is a need to provide long-term remote training and feedback. Particularly related to activities of daily living that create opportunities for effective and lasting rehabilitation for elderly and sufferers from chronic non-communicable diseases. The aim of the current review is to envision the remote training and monitoring of physical and cognitive aspects for adults with limited mobility, through the implementation of concurrent telehealth and exergame features using XR and wireless sensor technologies. (shrink)