(2013). Formal Models of Reasoning in Cognitive Psychology. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 1-3. doi: 10.1080/19462166.2013.767559.

We offer a model of moral reform and regeneration that involves a wrong-doer making two movements: on the one hand, he identifies with himself as the one who did the act, while he also intentionally moves away from that self (or set of desires and intentions) and moves toward a transformed identity. We see this model at work in the formal practice of contrition and reform in Christian and Buddhist rites. This paper is part of a broader project we (...) are undertaking on the philosophy of forgiveness. (shrink)

(2013). Hierarchical Bayesian models as formal models of causal reasoning. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 36-45. doi: 10.1080/19462166.2012.700321.

This paper studies the modelling of legal reasoning about evidence within general theories of defeasible reasoning and argumentation. In particular, Wigmore's method for charting evidence and its use by modern legal evidence scholars is studied in order to give a formal underpinning in terms of logics for defeasible argumentation. Two notions turn out to be crucial, viz. argumentation schemes and empirical generalisations.

The standard model of precedential constraint holds that a court is equally free to modify a precedent of its own and a precedent of a superior court—overruling aside, it does not differentiate horizontal and vertical precedents. This paper shows that no model can capture the U.S. doctrine of precedent without making that distinction. A precise model is then developed that does just that. This requires situating precedent cases in a formal representation of a hierarchical legal structure, and adjusting the (...) constraint that a precedent imposes based on the relationship of the precedent court and the instant court. The paper closes with suggestions for further improvements of the model. (shrink)

This paper studies the modelling of legal reasoning about evidence within general theories of defeasible reasoning and argumentation. In particular, Wigmore's method for charting evidence and its use by modern legal evidence scholars is studied in order to give a formal underpinning in terms of logics for defeasible argumentation. Two notions turn out to be crucial, viz. argumentation schemes and empirical generalisations.

Reasoning with cases has been a primary focus of those working in AI and law who have attempted to model legal reasoning. In this paper we put forward a formal model of reasoning with cases which captures many of the insights from that previous work. We begin by stating our view of reasoning with cases as a process of constructing, evaluating and applying a theory. Central to our model is a view of the relationship between (...) cases, rules based on cases, and the social values which justify those rules. Having given our view of these relationships, we present our formal model of them, and explain how theories can be constructed, compared and evaluated. We then show how previous work can be described in terms of our model, and discuss extensions to the basic model to accommodate particular features of previous work. We conclude by identifying some directions for future work. (shrink)

The doctrine of double effect is an ethical principle that can account for human judgment in moral dilemmas: situations in which all available options have large good and bad consequences. We have previously formalized \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {{DDE}}$$\end{document} in a computational logic that can be implemented in robots. \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {{DDE}}$$\end{document}, as an ethical principle for robots, is attractive for a number of reasons: Empirical studies (...) have found that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {{DDE}}$$\end{document} is used by untrained humans; many legal systems use \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {{DDE}}$$\end{document}; and finally, the doctrine is a hybrid of the two major opposing families of ethical theories. In spite of all its attractive features, we have found that \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {{DDE}}$$\end{document} does not fully account for human behavior in many ethically challenging situations. Specifically, standard \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {{DDE}}$$\end{document} fails in situations wherein humans have the option of self-sacrifice. Accordingly, we present an enhancement of our \documentclass[12pt]{minimal} \usepackage{amsmath} \usepackage{wasysym} \usepackage{amsfonts} \usepackage{amssymb} \usepackage{amsbsy} \usepackage{mathrsfs} \usepackage{upgreek} \setlength{\oddsidemargin}{-69pt} \begin{document}$$\mathcal {{DDE}}$$\end{document}-formalism to handle self-sacrifice; we end by looking ahead to future work. (shrink)

Many problems in Multi-Agent Systems (MASs) research are formulated in terms of the abilities of a coalition of agents. Existing approaches to reasoning about coalitional ability are usually focused on games or transition systems, which are described in terms of states and actions. Such approaches however often neglect a key feature of multi-agent systems, namely that the actions of the agents require resources. In this paper, we describe a logic for reasoning about coalitional ability under resource constraints in (...) the probabilistic setting. We extend Resource-bounded Alternating-time Temporal Logic (RB-ATL) with probabilistic reasoning and provide a standard algorithm for the model-checking problem of the resulting logic Probabilistic resource-bounded ATL (pRB-ATL). We implement model-checking algorithms and present experimental results using simple multi-agent model-checking problems of increasing complexity. (shrink)

Inspired by legal reasoning, this paper presents a formal framework for assessing conflicting arguments. Its use is illustrated with applications to realistic legal examples, and the potential for implementation is discussed. The framework has the form of a logical system for defeasible argumentation. Its language, which is of a logic-programming-like nature, has both weak and explicit negation, and conflicts between arguments are decided with the help of priorities on the rules. An important feature of the system is that (...) these priorities are not fixed, but are themselves defeasibly derived as conclusions within the system. Thus debates on the choice between conflicting arguments can also be modelled.The proof theory of the system is stated in dialectical style, where a proof takes the form of a dialogue between a proponent and an opponent of an argument. An argument is shown to be justified if the proponent can make the opponent run out of moves in whatever way the opponent attacks. Despite this dialectical form, the system reflects a declarative, or relational approach to modelling legal argument. A basic assumption of this paper is that this approach complements two other lines of research in AI and Law, investigations of precedent-based reasoning and the development of procedural, or dialectical models of legal argument. (shrink)

Quantum mechanics admits a “linguistic interpretation” if one equates preliminary any quantum state of some whether quantum entity or word, i.e. a wave function interpret-able as an element of the separable complex Hilbert space. All possible Feynman pathways can link to each other any two semantic units such as words or term in any theory. Then, the causal reasoning would correspond to the case of classical mechanics (a single trajectory, in which any next point is causally conditioned), and the (...) probabilistic reasoning, to the case of quantum mechanics (many Feynman trajectories). Frame semantics turns out to be the natural counterpart of that linguistic interpretation of quantum mechanics. (shrink)

John Broome has developed an account of rationality and reasoning which gives philosophical foundations for choice theory and the psychology of rational agents. We formalize his account into a model that differs from ordinary choice-theoretic models through focusing on psychology and the reasoning process. Within that model, we ask Broome’s central question of whether reasoning can make us more rational: whether it allows us to acquire transitive preferences, consistent beliefs, non-akratic intentions, and so on. We identify (...) three structural types of rationality requirements: consistency requirements, completeness requirements, and closedness requirements. Many standard rationality requirements fall under this typology. Based on three theorems, we argue that reasoning is successful in achieving closedness requirements, but not in achieving consistency or completeness requirements. We assess how far our negative results reveal gaps in Broome's theory, or deficiencies in choice theory and behavioral economics. (shrink)

This is the preface of the special Issue: Formal Representations in Model-based Reasoning and Abduction, published at the Logic Jnl IGPL (2012) 20 (2): 367-369. doi: 10.1093/jigpal/jzq055 First published online: December 20, 2010.

(2013). Statistical models as cognitive models of individual differences in reasoning. Argument & Computation: Vol. 4, Formal Models of Reasoning in Cognitive Psychology, pp. 89-102. doi: 10.1080/19462166.2012.674061.

The grammatical paradigm used to be a model for entire areas of cognitive science. Its primary tenet was that theories are axiomatic-like systems. A secondary tenet was that their predictions should be tested quickly and in great detail with introspective judgments. While the grammatical paradigm now often seems passé, we argue that in fact it continues to be as efficient as ever. Formal models are essential because they are explicit, highly predictive, and typically modular. They make numerous critical (...) predictions, which must be tested efficiently; introspective judgments do just this. We further argue that the grammatical paradigm continues to be fruitful. Within linguistics, implicature theory is a recent example, with a combination of formal explicitness, modularity, and interaction with experimental work. Beyond traditional linguistics, the grammatical paradigm has proven fruitful in the study of gestures and emojis; literature (“Free Indirect Discourse”); picture semantics and comics; music and dance cognition; and even reasoning and concepts. We argue, however, that the grammatical paradigm must be adapted to contemporary cognitive science. Computational methods are essential to derive quantitative predictions from formal models (Bayesian pragmatics is an example). And data collection techniques offer an ever richer continuum of options, from introspective judgments to large-scale experiments, which makes it possible to optimize the cost/benefit ratio of the empirical methods that are chosen to test theories. (shrink)

From its beginnings in Aristotle, logic was intended to account not only for reasoning that is theoretical (or conclusion-oriented), but for reasoning that is practical (or actionoriented). However, despite an interest in the topic that continues to the present, the practical side of reasoning has remained broadly speculative. At least in some domains (mathematics, in particular), there are well developed proof-theoretic and semantic theories that yield quite detailed models of correct reasoning, and these models (...) are useful for both theoretical and practical purposes. In contrast, the logical work on practical reasoning has remained broadly speculative and disengaged from applications. Logical formalisms have not been forthcoming that would be useful either in designing an agent that needs to act intelligently, or in helping an intelligent agent to evaluate its reasoning about action. (shrink)

Based on architectural projects which interpret literature as program we discuss design reasoning when no routine models of problem solving apply. We address three aspects of formulation: defining the design charge so that it can be retrospectively stated independent of the actual proposal; defining a language of formal operations; and defining the intrinsic aims of design that are only intimated through the proposal itself. The coherence of the project is a function of the way in which (...) class='Hi'>formal properties interact, and the way in which they sustain analogical or metaphorical relationships to text: how the patterns of subdivision, connection, differentiation, positioning, movement or perception associated with built space relate to textual figures, concepts, structure, or narrative. The possibility of constructing architectural meaning in this way implies an underlying model of space as a morphic language which works primarily through the constitution of generic and significant relationships rather than the combination of previously objectified elements. The gradual articulation of the design charge is mediated by a process of diagramming. Diagrams express as spatial constructions the conditions and concepts abstracted from text; also, they act as notations of constructive operations which are themselves spatial. Diagrams can be abstractive or pictorial, dense or discrete. They document two aspects of an integral process of reasoning: First, an exploration of how concepts, whether directly, analogically or metaphorically transferred from text to shape, may relate to produce a more complex idea; second, how formal properties co-vary and how an emergent design proposal engages and activates a field of formal possibility. (shrink)

Many weaknesses of game theory are cured by new models that embody simple cognitive principles, while maintaining the formalism and generality that makes game theory useful. Social preference models can generate team reasoning by combining reciprocation and correlated equilibrium. Models of limited iterated thinking explain data better than equilibrium models do; and they self-repair problems of implausibility and multiplicity of equilibria.

This volume is based on the papers presented at the international conference Model-Based Reasoning in Science and Technology (MBR09_BRAZIL), held at the University of Campinas (UNICAMP), Campinas, Brazil, December 2009. The presentations given at the conference explored how scientific cognition, but several other kinds as well, use models, abduction, and explanatory reasoning to produce important or creative changes in theories and concepts. Some speakers addressed the problem of model-based reasoning in technology, and stressed the issue of (...) science and technological innovation. The various contributions of the book are written by interdisciplinary researchers who are active in the area of creative reasoning in logic, science, and technology: the most recent results and achievements about the topics above are illustrated in detail in the papers. The book is divided in three parts, which cover the following main areas: part I, abduction, problem solving, and practical reasoning; part II: formal and computational aspects of model based reasoning; part III, models, mental models, representations. (shrink)

Logical models of argument formalize commonsense reasoning while taking process and computation seriously. This survey discusses the main ideas which characterize di erent logical models of argument. It presents the formal features of a few main approaches to the modeling of argumentation. We trace the evolution of argumentationfrom the mid-80's, when argumentsystems emerged as an alternative to nonmonotonic formalisms based on classical logic, to the present, as argument is embedded in di erent complex systems for real-world (...) applications, and allows more formal work to be done in different areas, such as AI & Law, case-based reasoning and negotiation among intelligent agents. (shrink)

In fields such as medicine, geography, and mechanics, spatial reasoning involves reasoning about entities that may coincide without overlapping. Some examples are: cavities and invading particles, passageways and valves, geographic regions and tropical storms. The purpose of this paper is to develop a formal theory of spatial relations for domains that include coincident entities. The core of the theory is a clear distinction between mereotopological relations, such as parthood and connection, and relative location relations, such as coincidence. (...) To guide the development of the formal theory, I construct mathematical models in which nontrivial relative location relations are defined. (shrink)

In this paper, I address a question in social epistemology about the unity of a scientic community to- wards its inner groups (teams, labs...). I investigate the reasons why these groups might want to \go it alone", working among themselves and hiding their discoveries from other groups. I concentrate on the intermediate results of a longer project, where the first steps can help to achieve a more advanced result. I study to what extent the isolation of research groups might be (...) damaging to the epistemic progress of the whole community. In order to get an idea of the reason why scientists might not share their intermediate results with others, consider for example Schawlow and Townes in the summer of 1958 (the historical material is drawn from Broberg, 1991, chap. 3): together they had just designed the principle of functioning of what would be known as the laser, with the intention of constructing the rst laser, relying on their theoretical ideas. Should they have published their theoretical discovery, or rather taken advantage of their advance on possible oppo- nents and start the experimental work? They chose to publish their theoretical ideas in a scientic journal, and they also led a patent application. On the one hand, it was a valuable choice: the patent was granted and their paper was published, making them soon famous. Further- more, another scientist called Gould was to le a simi- lar patent application a few months later, in March 1959; it was refused, because of the priority of Schawlow and Townes. If the latter had not submitted their idea in 1958, the patent would certainly have been acknowl- edged to Gould. In this sense, publishing their intermediate result was a worthy strategy. On the other hand, history showed that their publication had also some drawbacks for them. Schawlow and Townes' publication triggered a race among many American laboratories for the rst experimental construction of the laser. In addition to bringing them competitors, their publication helped these competitors in crucial ways; so much so that it was another scientist, Maiman, and not Schawlow and Townes, who was able to build the rst working laser, in May 1960, and to publish the result. If Schawlow and Townes had not published their theoretical idea, there are chances that they would have been the first ones to build a laser. Their publication of the first theoretical result certainly prevented them from getting the second experimental one. In short, the best publishing strategy about an intermediate result is no easy question for a scientist. Consider now the whole community, concerned with the results available to all and with the pace of the epistemic progress. Schawlow and Townes' publication enabled the rst laser to be built quicker, as other teams could rely on their theoretical work. More generally, being able to reuse other's works seems to be a rm basis of scientic progress. Thus, for the whole community, it seems that there are only benets if intermediate results are published. As this is not necessarily the best strategy for those who reach these intermediate results, there might be a conflict between the interests of individuals and those of the whole community. The question Schawlow and Townes faced was whether they should make their discovery publicly known, or keep it for themselves to progress alone. This alternative can also arise for an entire lab, when competing with other labs on some long-run project: should it make its discoveries known to its opponents, or only share them internally among its members? At a higher level still, this question arises for what can be called scientic schools, which are groups of labs sharing some particular approach|methodological, experimental or interpre- tational, for example. At each level within the scientic community, there are competitive groups of scientists which may decide to go it alone and to prevent their results from being accessible to others. If they had good reasons for doing so, there would be dramatic consequences for the whole community: other groups would not be able to reuse their results, labour force would be wasted in achieving them again, and the progress of the eld would be slowered. 9 The aim of this paper is to investigate this risk of division: to assess the conditions under which it may oc- cur, its damage for the community, and to draw the limit of an acceptable pluralism. The reasoning with benets and drawbacks which has been sketched for Schawlow and Townes seems to be implicitly an informal economic argument. In order to clarify and to rene such an argument, I will investigate it in a rational decision framework, supposing some utility or preferences for the groups of scientists, and I will propose a formal model, in game theory. In social epistemology of science, formal models have been proposed for various questions (for example, Kitcher 1990, 1993, Goldman 2009, Strevens 2003, 2006, Weisberg and Muldoon, forthcoming, Zollman 2007, 2008, 2009, 2010), but not for the question of the division of the scientic community. I will concentrate on the normative aspect of the question, ignoring the descriptive and historical question of whether groups do go it alone or not. The model I propose is sequential: two groups are competing on a research program, which consists of several results which have to be obtained in order. The groups always carry out some research for the next result, which they reach with some probability per unit of time. When a group, say A, reaches a result, it can either make it public for the other group, or continue its research. After a result is made public, the competitor B can start from it so as to continue its own research. Thus, when A publishes it loses its lead, and its competitor will be able to compete with it in the near future. But it is also recognized as the rst to reach this step. I consider two dierent cases, one in which the number of steps is limited, another where the limit concerns the number of temporal intervals. In both cases, assuming that all steps are equally dicult and equally rewarding, it turns out that the best strategy for a group concerned with its own reward is to make public every step it takes. Thus, there is no risk that groups might separate: a scientist, whatever its group, will publish for all. Finally, I turn to more complex situations, where results have varying size or diculty: there, groups can indeed be better o going it alone. (shrink)

The First International and Interdisciplinary Conference on Modelling and Using Context, Rio de Janeiro, January 1997, gave rise to the present book, which contains a selection of the papers presented there, thoroughly refereed and revised. The treatment of contexts as bona fide objects of logical formalisation has gained wide acceptance, following the seminal impetus given by McCarthy in his Turing Award address. The field of natural language offers a particularly rich variety of examples and challenges to researchers concerned with the (...) formal modelling of context, and several chapters in the volume deal with contextualisation in the setting of natural language. Others adopt a purely formal-logical viewpoint, seeking to develop general models of even wider applicability. The 12 chapters are organised in three groups: formalisation of contextual information in natural language understanding and generation, the application of context in mechanised reasoning domains, and novel non-classical logics for contextual application. (shrink)

Under the independence and competence assumptions of Condorcet’s classical jury model, the probability of a correct majority decision converges to certainty as the jury size increases, a seemingly unrealistic result. Using Bayesian networks, we argue that the model’s independence assumption requires that the state of the world (guilty or not guilty) is the latest common cause of all jurors’ votes. But often – arguably in all courtroom cases and in many expert panels – the latest such common cause is a (...) shared ‘body of evidence’ observed by the jurors. In the corresponding Bayesian network, the votes are direct descendants not of the state of the world, but of the body of evidence, which in turn is a direct descendant of the state of the world. We develop a model of jury decisions based on this Bayesian network. Our model permits the possibility of misleading evidence, even for a maximally competent observer, which cannot easily be accommodated in the classical model. We prove that (i) the probability of a correct majority verdict converges to the probability that the body of evidence is not misleading, a value typically below 1; (ii) depending on the required threshold of ‘no reasonable doubt’, it may be impossible, even in an arbitrarily large jury, to establish guilt of a defendant ‘beyond any reasonable doubt’. (shrink)

Many of our decisions pertain to causal systems. Nevertheless, only recently has it been claimed that people use causal models when making judgments, decisions and predictions, and that causal Bayes nets allow us to formally describe these inferences. Experimental research has been limited to simple, artificial problems, which are unrepresentative of the complex dynamic systems we successfully deal with in everyday life. For instance, in social interactions, we can explain the actions of other's on the fly and we can (...) generalize from limited observations to predict future actions and their consequences. Our main argument is that none of these inferences (i.e., induction, generalization, explanation, and prediction) can be achieved without causal reasoning. As a case in point we use the popular television series desperate housewives and show how causal Bayes nets are able to explain the inferences made in social contexts. Crucially, causal Bayes nets also allow us to understand why we can infer so much from so little when making sense of a protagonist's behavior. (shrink)

In this paper several recent factor- and dimension-based models of precedential constraint are formally investigated and an alternative dimension-based model is proposed. Simple factor- and dimension-based syntactic criteria are identified for checking whether a decision in a new case is forced, in terms of the relevant differences between a precedent and a new case, and the difference between absence of factors and negated factors in factor-based models is investigated. Then Horty’s and Rigoni’s recent dimension-based models of precedential (...) constraint are critically examined. An alternative to their reason models is proposed which is less expressive but arguably easier to apply in practice. (shrink)

Formal models of argumentation have been investigated in several areas, from multi-agent systems and artificial intelligence (AI) to decision making, philosophy and law. In artificial intelligence, logic-based models have been the standard for the representation of argumentative reasoning. More recently, the standard logic-based models have been shown equivalent to standard connectionist models. This has created a new line of research where (i) neural networks can be used as a parallel computational model for argumentation and (...) (ii) neural networks can be used to combine argumentation, quantitative reasoning and statistical learning. At the same time, non-standard logic models of argumentation started to emerge. In this paper, we propose a connectionist cognitive model of argumentation that accounts for both standard and non-standard forms of argumentation. The model is shown to be an adequate framework for dealing with standard and non-standard argumentation, including joint-attacks, argument support, ordered attacks, disjunctive attacks, meta-level attacks, self-defeating attacks, argument accrual and uncertainty. We show that the neural cognitive approach offers an adequate way of modelling all of these different aspects of argumentation. We have applied the framework to the modelling of a public prosecution charging decision as part of a real legal decision making case study containing many of the above aspects of argumentation. The results show that the model can be a useful tool in the analysis of legal decision making, including the analysis of what-if questions and the analysis of alternative conclusions. The approach opens up two new perspectives in the short-term: the use of neural networks for computing prevailing arguments efficiently through the propagation in parallel of neuronal activations, and the use of the same networks to evolve the structure of the argumentation network through learning (e.g. to learn the strength of arguments from data). (shrink)

This chapter is on when and how formalization and model building contribute to theory construction in methodological individualism. It shows that formalization is not always needed but can sometimes be useful for making assumptions explicit and for deriving implications that would appear out of reach of, or even go counter to, informal reasoning. The chapter focuses on examples from different theoretical approaches and research fields, including meanwhile ‘classic’ as well as more recent contributions. We sketch both insights that do (...) not require elaborate formalization as well as implications that do require some degree of formalization. The exposition itself is largely informal. (shrink)

The article considers two different interpretations of the reason model of precedent pioneered by John Horty. On a plausible interpretation of the reason model, past cases provide reasons to prioritize reasons favouring the same outcome as a past case over reasons favouring the opposing outcome. Here I consider the merits of this approach to the role of precedent in legal reasoning in comparison with a closely related view favoured by some legal theorists, according to which past cases provide reasons (...) for undercutting (or ‘excluding’) reasons favouring the opposing outcome. After embedding both accounts within a general default logic, I note some important differences between the two approaches that emerge as a result of plausible distinctions between rebutting and undercutting defeat in formal models of legal reasoning. These differences stem from the ‘preference independence’ of undercutting defeat. Undercutting reasons succeed in defeating opposing reasons irrespective of their relative strength. As a result, the two accounts differ in their account of the way in which precedents constrain judicial reasoning. I conclude by suggesting that the two approaches can be integrated within a single model, in which the distinction between undercutting and rebutting defeat is used to account for the distinction between strict and persuasive forms of precedential constraint. (shrink)

This paper offers a new model of belief by embedding the Peircean account of belief into a formal dialogue system that uses argumentation schemes for practical reasoning and abductive reasoning. A belief is characterised as a stable proposition that is derived abductively by one agent in a dialogue from the commitment set (including commitments derived from actions and goals) of another agent. On the model (to give a rough summary), a belief is defined as a proposition held (...) by an agent that (1) is not easily changed (stable), (2) is a matter of degree (held more or less weakly or strongly), (3) guides the goals and actions of the agent, and (4) is habitually or tenaciously held in a manner that indicates a strong commitment to defend it. It is argued that the new model overcomes the pervasive conflict in artificial intelligence between the belief-desire-intention model of reasoning and the commitment model. (shrink)

Charles Mills has argued against ideal theory in political philosophy on the basis that it contains idealizations. He calls for political philosophers to do more nonideal theory, namely political theory that pays more attention to the most visible oppressions in society, such as those based on race, gender, and class. Mills's argument relies on a distinction between idealization and abstraction. Idealizations involve adding false assumptions to one's model, which is unacceptable, whereas abstractions merely leave out details without undermining descriptive power. (...) By studying formal models of injustice, I argue that the idealization/abstraction distinction is unhelpful. Either the distinction exists only relative to one's modeling purposes, or all models in political theory contain idealizations. Either way, the distinction does not help Mills's cause. Furthermore, there are arguments from philosophy of science for the epistemic benefits of idealizations. However, Mills's call for greater emphasis on the most visible mechanisms of oppression can be supported without relying on an idealization/abstraction distinction. I provide three alternative reasons for why we should prefer political theories that place more emphasis on race-, class-, and gender-based oppression. (shrink)

In this paper we show that any reasoning process in which conclusions can be both fallible and corrigible can be formalized in terms of two approaches: (i) syntactically, with the use of defeasible reasoning, according to which reasoning consists in the construction and assessment of arguments for and against a given claim, and (ii) semantically, with the use of partial structures, which allow for the representation of less than conclusive information. We are particularly interested in the formalization (...) of scientific reasoning, along the lines traced by Lakatos’ methodology of scientific research programs. We show how current debates in cosmology could be put into this framework, shedding light on a very controversial topic. (shrink)

This paper sets out to show how mathematical modelling can serve as a way of ampliating knowledge. To this end, I discuss the mathematical modelling of time in theoretical physics. In particular I examine the construction of the formal treatment of time in classical physics, based on Barrow’s analogy between time and the real number line, and the modelling of time resulting from the Wheeler-DeWitt equation. I will show how mathematics shapes physical concepts, like time, acting as a heuristic (...) means—a discovery tool—, which enables us to construct hypotheses on certain problems that would be hard, and in some cases impossible, to understand otherwise. (shrink)

This paper addresses the problem posed by the current split between the two opposed hypotheses in the growing literature on the fallacy of begging the question the epistemic hypothesis, based on knowledge and belief, and the dialectical one, based on formal dialogue systems. In the first section, the nature of split is explained, and it is shown how each hypothesis has developed. To get the beginning reader up to speed in the literature, a number of key problematic examples are (...) analyzed illustrating how both approaches can be applied. Useful tools are brought to bear on them, including the automated argument diagramming system Araucaria, and profiles of dialogue used to represent circular argumentation in a dialogue tableau format. These tools are used to both to model circular reasoning and to provide the contextual evidence needed to properly determine whether the circular reasoning in a given case is better judged fallacious or not. A number of technical problems that have impeded the development of both hypotheses are studied. One central problem is the distinction between argument and explanation. It is concluded that the best way to move forward and solve these problems is to reformulate the two hypotheses in such a way that they might be able to co-exist. On this basis, a unified methodology is proposed that allows each hypothesis to move forward as a legitimate avenue for research using the same tools. (shrink)

The overall goal of this paper is to show that computational modelling of argumentation theories is a useful tool to deepen them. Specifically, it provides a basic computational formalization of part of Pragma-dialectics’ model of a critical discussion, which serves as a basis for analyzing this influential theory of argumentation. Such analysis reveals some weaknesses and leaves some questions opened for Pragma-dialectics. Particularly, it shows that the model of a critical discussion is not independent of the model of reasoning/inference (...) chosen, because, while it performs differently with different models of reasoning, it does not work well with some of them. (shrink)

John Stuart Mill advocated for increased interactions between individuals of dissenting opinions for the reason that it would improve society. Whether Mill and similar arguments that advocate for opinion diversity are valid depends on background assumptions about the psychology and sociality of individuals. The field of opinion dynamics is a burgeoning testing ground for how different combinations of sociological and psychological facts contribute to phenomena that affect opinion diversity, such as polarization. This paper applies some recent results from the opinion (...) dynamics literature to assess the impacts of the Millian suggestion. The goal is to understand how the scope of the validity of Mill-style arguments depends on plausible assumptions that can be formalized using agent-based models, a common modeling approach in opinion dynamics. The most salient insight is that homophily (increased interactions between like-minded individuals) does not sufficiently explain decreased opinion diversity. Hence, decreasing homophily by increasing interactions between individuals of dissenting opinions is not the simple solution that a Millian-style argument may advocate. (shrink)

The knowledge representation and reasoning of both humans and artificial systems often involves conditionals. A conditional connects a consequence which holds given a precondition. It can be easily recognized in natural languages with certain key words, like “if” in English. A vast amount of literature in both fields, both artificial intelligence and psychology, deals with the questions of how such conditionals can be best represented and how these conditionals can model human reasoning. On the other hand, findings in (...) the psychology of reasoning, such as those in the Suppression Task, have led to a paradigm shift from the monotonicity assumptions in human inferences towards nonmonotonic reasoning. Nonmonotonic reasoning is sensitive for information change, that is, inferences are drawn cautiously such that retraction of previous information is not required with the addition of new information. While many formalisms of nonmonotonic reasoning have been proposed in the field of Artificial Intelligence, their capability to model properties of human reasoning has not yet been extensively investigated. In this paper, we analyzed systematically from both a formal and an empirical perspective the power of formal nonmonotonic systems to model possible explicit defeaters, as in the Suppression Task, and more implicit conditional rules that trigger nonmonotonic reasoning by the keywords in such rules. The results indicated that the classical evaluation for the correctness of inferences has to be extended in the three major aspects regarding the inference system, the knowledge base, and possible assumed exceptions for the rule. (shrink)

:One view of practical reasoning is that it involves the weighing of reasons. It is not clear, however, how the weights of reasons combine, especially given the logical and substantive relations among different reasons. Nor is it clear how the weighing of reasons relates to decision theoretic maximization of expected value. This paper constructs a formal model of reasons and their weight in order to shed light on these issues. The model informs philosophical debates about reasons, such as (...) the question of whether reasons or values are more fundamental and the opposing doctrines of atomism and holism about reasons. (shrink)

Modelling with Words is an emerging modelling methodology closely related to the paradigm of Computing with Words introduced by Lotfi Zadeh. This book is an authoritative collection of key contributions to the new concept of Modelling with Words. A wide range of issues in systems modelling and analysis is presented, extending from conceptual graphs and fuzzy quantifiers to humanist computing and self-organizing maps. Among the core issues investigated are - balancing predictive accuracy and high level transparency in learning - scaling (...) linguistic algorithms to high-dimensional data problems - integrating linguistic expert knowledge with knowledge derived from data - identifying sound and useful inference rules - integrating fuzzy and probabilistic uncertainty in data modelling. (shrink)

A range of formal models of human reasoning have been proposed in a number of fields such as philosophy, logic, artificial intelligence, computer science, psychology, cognitive science, etc.: various logics, probabilistic systems, belief revision systems, neural networks, among others. Now, it seems reasonable to require that formal models of human reasoning be empirically adequate if they are to be viewed as models of the phenomena in question. How are formal models of (...) human reasoning typically put to empirical test? One way to do so is to isolate a number of key principles of the system, and design experiments to gauge the extent to which participants do or do not follow them in reasoning tasks. Another way is to take relevant existing results and check whether a particular formal model predicts these results. The present investigation provides an illustration of the second kind of empirical testing by comparing two formal models for reasoning – namely the non-monotonic logic known as preferential logic; and a particular version of belief revision theories, screened belief revision – against the reasoning phenomenon known as belief bias in the psychology of reasoning literature: human reasoners typically seek to maintain the beliefs they already hold, and conversely to reject contradicting incoming information. The conclusion of our analysis will be that screened belief revision is more empirically adequate with respect to belief bias than preferential logic and non-monotonic logics in general, as what participants seem to be doing is above all a form of belief management on the basis of background knowledge. The upshot is thus that, while it may offer valuable insights into the nature of human reasoning, preferential logic is ultimately inadequate as a formal model of the phenomena in question. (shrink)

This paper presents a new theory of modal reasoning, i.e. reasoning about what may or may not be the case, and what must or must not be the case. It postulates that individuals construct models of the premises in which they make explicit only what is true. A conclusion is possible if it holds in at least one model, whereas it is necessary if it holds in all the models. The theory makes three predictions, which are (...) corroborated experimentally. First, conclusions correspond to the true, but not the false, components of possibilities. Second, there is a key interaction: it is easier to infer that a situation is possible as opposed to impossible, whereas it is easier to infer that a situation is not necessary as opposed to necessary. Third, individuals make systematic errors of omission and of commission. We contrast the theory with theories based on formal rules. (shrink)

The scheme of concepts we employ in daily life to explain intentional behaviour form a belief-desire model, in which motivating states are sorted into two suitably broad categories. The BD model embeds a philosophy of action, i.e. a set of assumptions about the ontology of motivation with subsequent restrictions on psychologising and norms of practical reason. A comprehensive critique of those assumptions and implications is offered in this work, and various criticisms of the model are met. The model’s predictive and (...) explanatory value exploits realistic notions of beliefs and desires as inner states underlying behavioural patterns. It is argued that the popular explication that beliefs and desires differ in their “direction of fit” is insufficient and inescapably normative. Essential to the model is the causal role given to desires. ‘Desire’ is therefore focussed. A dispositional and functional characterisation of desires is compatible with an eliminative view of dispositions. These views taken together do not exclude regarding desires as causes. Desires have propositional content. Content is a feature of desire’s dispositionality, and thereby causally relevant. This functional characterisation of content allows for non-linguistic content. The phenomenal conception of desire is criticised and diagnosed. A theme defended in various ways throughout the work is that desires mostly are unknown to agents and that the agent is in a less privileged position when it comes to analysis of his own motivational states, than e.g. people close to him. There are formal and empirical reasons to be pessimistic about agents’ abilities to make reliable predictions about their own intentional behaviour. The BD model’s concept of ‘intention’ is discussed and compared with non-reductive views of intentions. Criticisms of the common view that David Hume defends a BD model are presented, but it is argued that the BD interpretation of Hume is plausible, although this reading requires important qualifications in order to preserve internal consistency. The BD model leaves room for focussing attention, making foregrounded practical judgements, higher order desiring and other activities affecting one’s decision process. However, these various forms of deliberation in many cases are overrated. Three suggested norms of internal structural rationality are criticised in favour of simple Humean instrumentalism about practical reason. That position implies that criticism of other people’s ultimate ends is not a matter of internal rationality, but an inevitably social practice; it is dependent upon our concern for others, our view of their social roles and our own intrinsic desires. (shrink)

Documented ethical violations and empirical research have demonstrated that, despite professional standards and formal training in ethical principles, some psychotherapists engage in unethical behaviors that compromise the welfare of clients. It appears that competing values and interests that emerge in the therapeutic endeavor can interfere with therapists' considerations of ethical standards and their willingness to act ethically. Expanding current models of ethical decision making, this article offers a hermeneutic model that recognizes that in addition to moral reasoning, (...) the context of the therapeutic relationship and the therapist's subjective responses are fundamental considerations in the interpretation and application of ethical interventions. Implications for understanding and training of ethics in psychotherapy in this broader context are explored. (shrink)

The collapse models of arithmetic are inconsistent, nontrivial models obtained from ℕ and set out in the Logic of Paradox (LP). They are given a general treatment by Priest (Priest, 2000). Finite collapse models are decidable, and thus axiomatizable, because finite. LP, however, is ill-suited to normal axiomatic reasoning, as it invalidates Modus Ponens, and almost all other usual conditional inferences. I set out a logic, A3, first given by Avron (Avron, 1991), and give a first (...) order axiom system for the finite collapse models. I present some standard arithmetical axioms in addition to a cyclic axiom and prove that these axioms are sound and complete for the cyclic models, reporting a similar result for the heap models. The state of the situation for the each of the kinds of infinite collapse model is, however, left an open question. (shrink)

The paper introduces, compares and contrasts formal models of source reliability proposed in the epistemology literature, in particular the prominent models of Bovens and Hartmann and Olsson :127–143, 2011). All are Bayesian models seeking to provide normative guidance, yet they differ subtly in assumptions and resulting behavior. Models are evaluated both on conceptual grounds and through simulations, and the relationship between models is clarified. The simulations both show surprising similarities and highlight relevant differences between (...) these models. Most importantly, however, our evaluations reveal that important normative concerns arguably remain unresolved. The philosophical implications of this for testimony are discussed. (shrink)

An organizing theme of the dissertation is the issue of how to make philosophical theories useful for scientific purposes. An argument for the contention is presented that it doesn’t suffice merely to theoretically motivate one’s theories, and make them compatible with existing data, but that philosophers having this aim should ideally contribute to identifying unique and hard to vary predictions of their theories. This methodological recommendation is applied to the ranking-theoretic approach to conditionals, which emphasizes the epistemic relevance and the (...) expression of reason relations as part of the semantics of the natural language conditional. As a first step, this approach is theoretically motivated in a comparative discussion of other alternatives in psychology of reasoning, like the suppositional theory of conditionals, and novel approaches to the problems of compositionality and accounting for the objective purport of indicative conditionals are presented. In a second step, a formal model is formulated, which allows us to derive quantitative predictions from the ranking-theoretic approach, and it is investigated which novel avenues of empirical research that this model opens up for. Finally, a treatment is given of the problem of logical omniscience as it concerns the issue of whether ranking theory (and other similar approaches) makes too idealized assumptions about rationality to allow for interesting applications in psychology of reasoning. Building on the work of Robert Brandom, a novel solution to this problem is presented, which both opens up for new perspectives in psychology of reasoning and appears to be capable of satisfying a range of constraints on bridge principles between logic and norms of reasoning, which would otherwise stand in a tension. (shrink)