This thesis studies the role of conceptual content in inference and reasoning. The first two chapters offer a theoretical and historical overview of the relation between inference and meaning in philosophy and psychology. In particular, a critical analysis of the formality thesis, i.e., the idea that rational inference is a rule-based and topic-neutral mechanism, is advanced. The origins of this idea in logic and its influence in philosophy and cognitive psychology are discussed. Chapter 3 consists of an analysis of the (...) relationship between inference and representation. It is argued that inference has to be studied from a pluralistic per- spective due to its dependence on different formats of representing information. The following four chapters apply conceptual spaces, a formal theory of concepts within cognitive semantics, to three concept-based inference-types. First, an explication of Sellars notion of material inference is advanced. Later, the model is extended to account for nonmonotonic inference by studying the role expectations in reasoning. Finally, a conceptual space-model of category-based induction is presented. This model predicts most of the empirical properties of this psychological phenomenon and subsumes some of the previous theories in psychology. It is stated that the explanatory fruitfulness of this new approach is evidence for the failure of the formality thesis and calls for a unified model of rational inference that puts semantics at center stage. The last chapter of the thesis discusses how inference and concepts interact in scientific reasoning, which makes constant use of hybrid symbolic structures for representing conceptual information. Stephen Toulmin’s notions of method of representation and inferential technique are developed and applied in a case study about the emergence of the notion of instantaneous speed during the passage from geometrical physics to analytical mechanics. It is claimed that this analysis provides support to the pluralistic perspective for theorizing about reasoning. (shrink)

Jeffrey Friedman’s Power Without Knowledge argues forcefully that there are inherent limitations to the predictability of human action, due to a circumstance he calls “ideational heterogeneity.” However, our resources for predicting human action somewhat reliably in the light of ideational heterogeneity have not been exhausted yet, and there are no in-principle barriers to progress in tackling the problem. There are, however, other strong reasons to think that disagreement among epistocrats is bound to persist, such that it will be difficult to (...) decide who has “the right answer” to a given technocratic problem. These reasons have to do with competing visions of the good society, fact/value entanglement, and the fragility of the facts of the social sciences. (shrink)

For all the recent discoveries of behavioral psychology and experimental economics, the spirit of homo economicus still dominates the contemporary disciplines of economics, political science, and sociology. Turning back to the earliest chapters of political economy, however, reveals that pioneering figures such as Francis Bacon, Thomas Hobbes, and Adam Smith were hardly apostles of economic rationality as they are often portrayed in influential narratives of the development of the social sciences. As we will see, while all three of these thinkers (...) can plausibly be read as endorsing “rationality,” they were also well aware of the systematic irrationality of human conduct, including a remarkable number of the cognitive biases later “discovered” by contemporary behavioral economists. Building on these insights I offer modest suggestions for how these thinkers, properly understood, might carry the behavioral revolution in different directions than those heretofore suggested. (shrink)

The Condorcet Jury Theorem, along with empirical results, establishes the accuracy of majority voting in a broad range of conditions. Here we investigate whether naïve participants (in the U.S. and...

Safety theorists prefer a strong version of safety over a weak version, in order to account for our intuition that we do not know lottery propositions. I argue that weak safety has advantages that can outweigh our intuitions in lottery cases. First, I argue that for the nonepistemic domain, we should adopt weak safety to account for experts’ claims about cyber security. Second, I argue that a unified account of safety is preferable. Hence, we should adopt weak safety for the (...) epistemic domain as well. My argument can also be put as follows. It is more plausible to suppose that our intuitions about lottery cases are misguided than to suppose either that experts’ judgments about cyber security are misguided or that there are different versions of safety. (shrink)

Multiple epistemological programs make use of intuitive judgments pertaining to an individual’s ability to gain knowledge from exclusively probabilistic/statistical information. This paper argues that these judgments likely form without deference to such information, instead being a function of the degree to which having knowledge is representative of an agent. Thus, these judgments fit the pattern of formation via a representativeness heuristic, like that famously described by Kahneman and Tversky to explain similar probabilistic judgments. Given this broad insensitivity to probabilistic/statistical information, (...) it directly follows that these epistemic judgments are insensitive to a given agent’s epistemic status. From this, the paper concludes that, breaking with common epistemological practice, we cannot assume that such judgments are reliable. (shrink)

Explanationist accounts of rational legal proof view trials as a competition between explanations. Such accounts are often criticized for being underdeveloped. One question in need of further attention is when guilt is proven beyond a reasonable doubt in criminal trials. This article defends an inference to the best explanation -based approach on which guilt is only established BARD if the best guilt explanation in a case is substantially more plausible than any innocence explanation, and there is no good reason to (...) presume that we have overlooked evidence or alternative explanations that could realistically have exonerated the defendant. This is a comparative account, which I argue is better suited for arriving at accurate verdicts than the non-comparative ‘no plausible alternative’ account that many explanationists tacitly assume. Furthermore, this account is not susceptible to the most important arguments against IBE in criminal trials or to arguments against other, non-explanationist interpretations of the BARD standard. I use a case study to illustrate how this account provides meaningful guidance for decision makers in criminal trials. (shrink)

Recent work in social epistemology has shown that, in certain situations, less communication leads to better outcomes for epistemic groups. In this paper, we show that, ceteris paribus, a Bayesian agent may believe less strongly that a single agent is biased than that an entire group of independent agents is biased. We explain this initially surprising result and show that it is in fact a consequence one may conceive on the basis of commonsense reasoning.

The widespread use of online search engines to answer the general public’s needs for information has raised concerns about possible biases and the emerging of a ‘filter bubble’ in which users are isolated from attitude-discordant messages. Research is split between approaches that largely focus on the intrinsic limitations of search engines and approaches that investigate user search behavior. This work evaluates the findings and limitations of both approaches and advances a theoretical framework for empirical investigations of cognitive biases in online (...) search activities about health-related topics. We aim to investigate the interaction between the user and the search engine as a whole. Online search activity about health-related topics is considered as a hypothesis-testing process. Two questions emerge: whether the retrieved information provided by the search engines are fit to fulfill their role as evidence, and whether the use of this information by users is cognitively and epistemologically valid and unbiased. (shrink)

We propose a coherence account of the conjunction fallacy applicable to both of its two paradigms. We compare our account with a recent proposal by Tentori et al. : 235–255, 2013) that attempts to generalize earlier confirmation accounts. Their model works better than its predecessors in some respects, but it exhibits only a shallow form of generality and is unsatisfactory in other ways as well: it is strained, complex, and untestable as it stands. Our coherence account inherits the strength of (...) the confirmation account, but in addition to being applicable to both paradigms, it is natural, simple, and readily testable. It thus constitutes the next natural step for Bayesian theorizing about the conjunction fallacy. (shrink)

Since the early 1980s, logical theories of belief revision have offered formal methods for the transformation of knowledge bases or “corpora” of data and beliefs. Early models have dealt with unconditional acceptance and integration of potentially belief-contravening pieces of information into the existing corpus. More recently, models of “non-prioritized” revision were proposed that allow the agent rationally to refuse to accept the new information. This paper introduces a refined method for changing beliefs by specifying constraints on the relative plausibility of (...) propositions. Like the earlier belief revision models, the method proposed is a qualitative one, in the sense that no numbers are needed in order to specify the posterior plausibility of the new information. We use reference beliefs in order to determine the degree of entrenchment of the newly accepted piece of information. We provide two kinds of semantics for this idea, give a logical characterization of the new model, study its relation with other operations of belief revision and contraction, and discuss its intuitive strengths and weaknesses. (shrink)

Some naturalistic philosophers of mind subscribing to the predictive processing theory of mind have adopted a realist attitude towards the results of Bayesian cognitive science. In this paper, we argue that this realist attitude is unwarranted. The Bayesian research program in cognitive science does not possess special epistemic virtues over alternative approaches for explaining mental phenomena involving uncertainty. In particular, the Bayesian approach is not simpler, more unifying, or more rational than alternatives. It is also contentious that the Bayesian approach (...) is overall better supported by the empirical evidence. So, to develop philosophical theories of mind on the basis of a realist interpretation of results from Bayesian cognitive science is unwarranted. Naturalistic philosophers of mind should instead adopt an anti-realist attitude towards these results and remain agnostic as to whether Bayesian models are true. For continuing on with an exclusive focus and praise of Bayes within debates about the predictive processing theory will impede progress in philosophical understanding of scientific practice in computational cognitive science as well as of the architecture of the mind. (shrink)

In this paper, I defend Non-Inferentialism about mental states, the view that we can perceive some mental states in a direct, non-inferential way. First, I discuss how the question of mental state perception is to be understood in light of recent debates in the philosophy of perception, and reconstruct Non-Inferentialism in a way that makes the question at hand—whether we can perceive mental states or not—scientifically tractable. Next, I motivate Non-Inferentialism by showing that under the assumption of the widely-accepted Principle (...) of Cognitive Economy, any account that treats mental state perception as an inferential process commits itself to an unrealistically inefficient picture of our cognitive architecture. Drawing on research in cognitive science, I will then show that my Non-Inferentialist view receives direct support by the available empirical evidence. I conclude that there is no psychologically relevant sense in which perception of mental states differs from paradigmatic cases of perception, such as the perception of ordinary objects. (shrink)

Dans cet article, je décris une partie de l’histoire des travaux sur le raisonnement humain mené par les philosophes et les psychologues en psychologie expérimentale. Ce travail interdisciplinaire particulier est intéressant, car il montre de quelles façons la recherche interdisciplinaire peut solidifier certaines idées préconçues omniprésentes dans un domaine particulier. Les travaux en psychologie expérimentale ont démontré que certains systèmes normatifs ne parviennent pas à modéliser le raisonnement dans des contextes de langage naturel. J’affirmerai, par conséquent, que les philosophes devraient (...) se servir de cette recherche psychologique comme motivation pour modifier ces modèles normatifs ou changer radicalement nos idées sur la manière dont ces modèles sont appliqués au raisonnement en langage naturel. (shrink)

Analogical reasoning is often employed in problem-solving and metaphor interpretation. This paper submits that, as a default, analogical reasoning addressing these different tasks employs different mapping strategies: In problem-solving, it employs analogy-maximising strategies (like structure mapping, Gentner & Markman 1997); in metaphor interpretation, analogy-minimising strategies (like ATT-Meta, Barnden 2015). The two strategies interact in analogical reasoning with conceptual metaphors. This interaction leads to predictable fallacies. The paper supports these hypotheses through case-studies on ‘mind’-metaphors from ordinary discourse, and abstract problem-solving in (...) the philosophy of mind, respectively: It shows that (1) default metaphorical interpretations for vision- and space-cognition metaphors can be derived with a variant of the analogy-minimising ATT-Meta approach, (2) philosophically influential introspective conceptions of the mind can be derived with conceptual metaphors only through an analogy-maximising strategy, and (3) the interaction of these strategies leads to hitherto unrecognised fallacies in analogical reasoning with metaphors. This yields a debunking explanation of introspective conceptions. (shrink)

In Exploitation: What It Is and Why It's Wrong (2003), I argued that the major non‐Marxist “ethically thick” approaches to exploitation were not successful in capturing what we find morally objectionable in paradigmatic cases of exploitation. My argument there focused on the consequentialist account of exploitation defended by Robert Goodin. Here I revisit the question of whether the recent multi‐level act consequentialist account of exploitation defended by Richard Arneson is successful. I raise questions about the nature of the account, and (...) conclude that it is a possibly coherent and ultimately inadequate account of the wrongness of exploitation. (shrink)

This chapter presents a new semantics for inductive empirical knowledge. The epistemic agent is represented concretely as a learner who processes new inputs through time and who forms new beliefs from those inputs by means of a concrete, computable learning program. The agent’s belief state is represented hyper-intensionally as a set of time-indexed sentences. Knowledge is interpreted as avoidance of error in the limit and as having converged to true belief from the present time onward. Familiar topics are re-examined within (...) the semantics, such as inductive skepticism, the logic of discovery, Duhem’s problem, the articulation of theories by auxiliary hypotheses, the role of serendipity in scientific knowledge, Fitch’s paradox, deductive closure of knowability, whether one can know inductively that one knows inductively, whether one can know inductively that one does not know inductively, and whether expert instruction can spread common inductive knowledge—as opposed to mere, true belief—through a community of gullible pupils. (shrink)

This volume presents research that integrates decision making and creativity within the social contexts in which these processes occur. The volume is an essential addition to and expansion of recent approaches to decision making. Such approaches attempt to incorporate more of the psychological and socio-cultural context in which human decision making takes place. The authors come from different disciplines and also belong to a broad spectrum of research traditions. They present innovative chapters dealing with both theoretical and empirical aspects of (...) decision making in different personal and organizational contexts. All chapters are written from the perspective that human decision making is inherently social and more or less creative. The volume addresses fundamental questions about the nature of human decision making as it occurs in different social contexts. Thereby, it becomes essential reading for researchers in decision making and for advanced students in psychology, management science, informatics, and related disciplines. (shrink)

Bayesian reasoning, defined here as the updating of a posterior probability following new information, has historically been problematic for humans. Classic psychology experiments have tested human Bayesian reasoning through the use of word problems and have evaluated each participant’s performance against the normatively correct answer provided by Bayes’ theorem. The standard finding is of generally poor performance. Over the past two decades, though, progress has been made on how to improve Bayesian reasoning. Most notably, research has demonstrated that the use (...) of frequencies in a natural sampling framework —as opposed to single-event probabilities—can improve participants’ Bayesian estimates. Furthermore, pictorial aids and certain individual difference factors also can play significant roles in Bayesian reasoning success. The mechanics of how to build tasks which show these improvements is not under much debate. The explanations for why naturally-sampled frequencies and pictures help Bayesian reasoning remain hotly contested, however, with many researchers falling into ingrained “camps” organized around two dominant theoretical perspectives. The present paper evaluates the merits of these theoretical perspectives, including the weight of empirical evidence, theoretical coherence, and predictive power. By these criteria, the ecological rationality approach is clearly better than the heuristics and biases view. Progress in the study of Bayesian reasoning will depend on continued research that honestly, vigorously, and consistently engages across these different theoretical accounts rather than staying “siloed” within one particular perspective. The process of science requires an understanding of competing points of view, with the ultimate goal being integration. (shrink)

ABSTRACTProbability judgements entail a conjunction fallacy if a conjunction is estimated to be more probable than one of its conjuncts. In the context of predication of alternative logical hypothesis, Bayesian logic provides a formalisation of pattern probabilities that renders a class of pattern-based CFs rational. BL predicts a complete system of other logical inclusion fallacies. A first test of this prediction is investigated here, using transparent tasks with clear set inclusions, varying in observed frequencies only. Experiment 1 uses data where (...) BL makes dominant predictions; Experiment 2's predictions were less clear, and we additionally investigated judgements about the second-most probable hypotheses. The results corroborated a pattern-probability account and cannot be easily explained by other theories of CFs. IFs were not limited to conjunctions, but rather occurred systematically for several logical connectives. Thus, pattern-based prob... (shrink)

Nonmonotonic reasoning is often claimed to mimic human common sense reasoning. Only a few studies, though, have investigated this claim empirically. We report four experiments which investigate three rules of SYSTEMP, namely the AND, the LEFT LOGICAL EQUIVALENCE, and the OR rule. The actual inferences of the subjects are compared with the coherent normative upper and lower probability bounds derived from a non-infinitesimal probability semantics of SYSTEM P. We found a relatively good agreement of human reasoning and principles of nonmonotonic (...) reasoning. Contrary to the results reported in the ‘heuristics and biases’ tradition, the subjects committed relatively few upper bound violations (conjunction fallacies). (shrink)

Causal reasoning is one of our most central cognitive competencies, enabling us to adapt to our world. Causal knowledge allows us to predict future events, or diagnose the causes of observed facts. We plan actions and solve problems using knowledge about cause-effect relations. Without our ability to discover and empirically test causal theories, we would not have made progress in various empirical sciences. In the past decades, the important role of causal knowledge has been discovered in many areas of cognitive (...) psychology. Despite the ubiquity of causal reasoning, textbooks of cognitive psychology have neglected this growing field. The goal of The Oxford Handbook of Causal Reasoning is to fill this gap. The handbook brings together the leading researchers in the field of causal reasoning and offers state-of-the-art presentations of theories and research. It provides introductions of competing theories of causal reasoning, and discusses its role in various cognitive functions and domains. The final section presents research from neighboring fields. 1. Causal Reasoning: An Introduction Michael R. Waldmann Part I: Theories of Causal Cognition 2. Associative Accounts of Causal Cognition Mike E. Le Pelley, Oren Griffiths, and Tom Beesley 3. Rules of Causal Judgment: Mapping Statistical Information Onto Causal Beliefs José C. Perales, Andrés Catena, Antonio Cándido, and Antonio Maldonado 4. The Inferential Reasoning Theory of Causal Learning: Toward a Multi- Process Propositional Account Yannick Boddez, Jan De Houwer, and Tom Beckers 5. Causal Invariance as an Essential Constraint for Creating a Causal Representation of the World: Generalizing the Invariance of Causal Power Patricia W. Cheng and Hongjing Lu 6. The Acquisition and Use of Causal Structure Knowledge Benjamin Margolin Rottman 7. Formalizing Prior Knowledge in Causal Induction Thomas L. Griffiths 8. Causal Mechanisms Samuel G. B. Johnson and Woo-kyoung Ahn 9. Force Dynamics and Causation Phillip Wolff and Robert Thorstad 10. Mental Models and Causation P. N. Johnson- Laird and Sangeet S. Khemlani 11. Pseudocontingencies Klaus Fiedler and Florian Kutzner 12. Singular Causation David Danks 13. Cognitive Neuroscience of Causal Reasoning Joachim T. Operskalski and Aron K. Barbey Part II: Basic Cognitive Functions 14. Visual Impressions of Causality Peter White 15. Goal-Directed Actions Bernhard Hommel 16. Planning and Control Magda Osman 17. Reinforcement Learning and Causal Models Samuel J. Gershman 18. Causation and the Probability of Causal Conditionals David E. Over 19. Causal Models and Conditional Reasoning Mike Oaksford and Nick Chater 20. Concepts as Causal Models: Categorization Bob Rehder 21. Concepts as Causal Models: Induction Bob Rehder 22. Causal Explanation Tania Lombrozo and Nadya Vasilyeva 23. Diagnostic Reasoning Björn Meder and Ralf Mayrhofer 24. Inferring Causal Relations by Analogy Keith J. Holyoak and Hee-Seung Lee 25. Causal Argument Ulrike Hahn, Roland Bluhm, and Frank Zenker 26. Causality in Decision- Making York Hagmayer and Philip M. Fernbach Part III: Domains of Causal Reasoning 27. Intuitive Theories Tobias Gerstenberg and Joshua B. Tenenbaum 28. Space, Time, and Causality Marc J. Buehner 29. Causation in Legal and Moral Reasoning David A. Lagnado and Tobias Gerstenberg 30. The Role of Causal Knowledge in Reasoning About Mental Disorders Woo-kyoung Ahn, Nancy S. Kim, and Matthew S. Lebowitz 31. Causality and Causal Reasoning in Natural Language Torgrim Solstad and Oliver Bott 32. Social Attribution and Explanation Denis Hilton Part IV: Development, Phylogeny, and Culture 33. The Development of Causal Reasoning Paul Muentener and Elizabeth Bonawitz 34. Causal Reasoning in Non-Human Animals Christian Schloegl and Julia Fischer 35. Causal Cognition and Culture Andrea Bender, Sieghard Beller, and Douglas L. Medin. (shrink)

El problema de marco cuestiona cómo los procesos cognitivos determinan qué información, de entre toda la disponible, es relevante dada una tarea determinada. Aunque postulamos una definición posible, especificar de qué trata este problema es una tarea complicada. Una manera de obtener claridad sobre esta cuestión es explorar distintas interpretaciones del problema de marco, interpretación lógica y filosófica, para dilucidar luego la dificultad en común. Como resultado de nuestro análisis concluimos que, sea la interpretación del problema de marco que se (...) tenga en mente, la dificultad subyacente es la misma: examinar vasta cantidad de información. La dificultad de la vastedad de información, a modo de puente entre ambas interpretaciones, permitiría no solo comprender más claramente de qué trata el problema de marco sino también resolverlo. The frame problem questions how cognitive processes determine what information is relevant, among all available, given a particular task. Although we proposed a possible definition, it is a difficult task to specify what this problem is about. One way to get insight into this matter is to explore different interpretations of the frame problem, a logical interpretation and a philosophical interpretation, to then elucidate the difficulty in common. The conclusion drawn from our analysis is that, irrespective of the interpretation of the frame problem you may have in mind, the underlying difficulty is the same: to examine a vastness of information. The difficulty posed by the vastness of information, taken as a bridge between both interpretations, would not only allow a clearer insight into the frame problem but also to solve it. (shrink)

Theory-ladenness of perception and cognition is pervasive and variable. Emerging maturationally natural perception and cognition, which are on-line, fast, automatic, unconscious, and, by virtue of their selectivity, theoretical in import, if not in form, define normal development. They contrast with off-line, slow, deliberate, conscious perceptual and cognitive judgments that reflective theories, including scientific ones, inform. Although culture tunes MN systems, their emergence and operation do not rely on culturally distinctive inputs. The sciences advance radically counter-intuitive representations that depart drastically from (...) MN systems’ deliverances. Extensive experience with RCI scientific theories can result in a practiced naturalness with their perceptual and cognitive consequences; nevertheless, automatic MN verdicts persistently intrude. Fodor suggests that the uniformity of the biases MN systems introduce can serve as a theory-neutral means for adjudicating scientific disputes. Findings about vision challenge Fodor’s proposal for circumventing problems that MN theory-ladenness presents. These considerations indicate that RCI scientific ideas are difficult to learn, master, and deploy; consequently, the corrective import of science’s social and institutional arrangements plays a critical role in its epistemic stature. (shrink)

Among the tools the epistemologist brings to the table ought to be, I suggest, a firm understanding of the imagination--one that is informed by philosophy of mind, cognitive psychology, and neuroscience. In my dissertation, I highlight several ways in which such an understanding of the imagination can yield insight into traditional questions in epistemology. My dissertation falls into three parts. In Part I, I argue that dreaming should be understood in imaginative terms, and that this has important implications for questions (...) about dream skepticism. In Part II, I argue that an understanding of the imagination is important for understanding important parts of philosophical methodology--particularly those involving thought experiments. I mean in Part II to be vindicating a great deal of traditional methodology. In Part III, I explore what I take to be a number of deep connections between knowledge and counterfactuals. I defend a form of contextualism in each domain, and argue that inference among imaginings, with its important structural similarities to inference in belief, plays a central role in the epistemology of counterfactuals. (shrink)

We describe a dual-process theory of how individuals estimate the probabilities of unique events, such as Hillary Clinton becoming U.S. President. It postulates that uncertainty is a guide to improbability. In its computer implementation, an intuitive system 1 simulates evidence in mental models and forms analog non-numerical representations of the magnitude of degrees of belief. This system has minimal computational power and combines evidence using a small repertoire of primitive operations. It resolves the uncertainty of divergent evidence for single events, (...) for conjunctions of events, and for inclusive disjunctions of events, by taking a primitive average of non-numerical probabilities. It computes conditional probabilities in a tractable way, treating the given event as evidence that may be relevant to the probability of the dependent event. A deliberative system 2 maps the resulting representations into numerical probabilities. With access to working memory, it carries out arithmetical operations in combining numerical estimates. Experiments corroborated the theory's predictions. Participants concurred in estimates of real possibilities. They violated the complete joint probability distribution in the predicted ways, when they made estimates about conjunctions: P, P, P, disjunctions: P, P, P, and conditional probabilities P, P, P. They were faster to estimate the probabilities of compound propositions when they had already estimated the probabilities of each of their components. We discuss the implications of these results for theories of probabilistic reasoning. (shrink)

The adequacy of similarity to prototype as an account of categorization in natural concepts was assessed by analyzing the monotonicity of the relation between typicality of an item in a category and the probability of a positive categorization response using data from McCloskey and Glucksberg (1978). The analysis revealed a strong underlying similarity-based threshold curve, with systematic deviations. Further data collection showed that deviations from the curve could be attributed to the effects of unfamiliarity and non-categorial associations on typicality judgments, (...) as well as differences between the perceptual appearance of an item (which tended to boost typicality) and its underlying nature (which tended to boost categorization). The results are discussed in terms of the different presuppositions and task constraints involved in rating typicality as opposed to performing a categorization. (shrink)

Can the output of human cognition be predicted from the assumption that it is an optimal response to the information-processing demands of the environment? A methodology called rational analysis is described for deriving predictions about cognitive phenomena using optimization assumptions. The predictions flow from the statistical structure of the environment and not the assumed structure of the mind. Bayesian inference is used, assuming that people start with a weak prior model of the world which they integrate with experience to develop (...) stronger models of specific aspects of the world. Cognitive performance maximizes the difference between the expected gain and cost of mental effort. Memory performance can be predicted on the assumption that retrieval seeks a maximal trade-off between the probability of finding the relevant memories and the effort required to do so; in categorization performance there is a similar trade-off between accuracy in predicting object features and the cost of hypothesis formation; in casual inference the trade-off is between accuracy in predicting future events and the cost of hypothesis formation; and in problem solving it is between the probability of achieving goals and the cost of both external and mental problem-solving search. The implemention of these rational prescriptions in neurally plausible architecture is also discussed. (shrink)

When base rates are learned and used in an experiential manner subjects show better base rate use, perhaps because the implicit learning system is engaged. A causal framework in which base rates are relevant might also be necessary. Humans might thus perform better on more ecologically valid tasks, which are likely to contain those three components.

The base rate fallacy is directly dependent on a particular judgment paradigm in which information may be unambiguously designated as either “base rate” or “individuating,” and in which subjects make two-stage sequential judgments. The paradigm may be a poor match for real world settings, and the fallacy may thus be undefined for natural ecologies of judgment.

This commentary questions Elqayam & Evans' (E&E's) claims that thinking tasks are doomed to have multiple normative readings and that only applied research allows normative evaluations. In fact, some tasks have just one undisputed normative reading, and not only pathological gamblers but also normal individuals sometimes need normative guidance. To conclude, normative evaluations are inevitable in the investigation of human thinking.

What role does moral reasoning play in moral judgment? More specifically, what causal role does moral reasoning have in the production of moral judgments? Recently, many philosophers and psychologists have attempted to answer this question by drawing on empirical data. However, these attempts fall short because there has been no sustained attention to the question of what moral reasoning is. This paper addresses this problem, by providing a general account of moral reasoning in terms of a capacity, and suggests how (...) this account of moral reasoning can provide a way forward in current debates. (shrink)

Language use and interpretation is heavily contingent on context. But human interlocutors need not always agree what the actual context is. In game theoretic approaches to language use and interpretation, interlocutors’ beliefs about the context are the players’ beliefs about the game that they are playing. Together this entails that we need to consider cases in which interlocutors have different subjective conceptualizations of the game they are in. This paper therefore extends iterated best response reasoning, as an established model for (...) pragmatic reasoning, to games with unawareness. This extension not only leads to more plausible context models for many communicative situations, but also to improved predictions for otherwise problematic cases and an extension of the scope of pragmatic phenomena that can be captured by game theoretic analysis. (shrink)

Five experiments investigated how people use categories to make inductions about objects whose categorisation is uncertain. Normatively, they should consider all the categories the object might be in and use a weighted combination of information from all the categories: bet-hedging. The experiments presented people with simple, artificial categories and asked them to make an induction about a new object that was most likely in one category but possibly in another. The results showed that the majority of people focused on the (...) most likely category in making inductions, although there was a group of consistently normative responders who used information from both categories (about 25% of our college population). Across experiments the overall pattern of results suggests that performance in the task is improved not by understanding the underlying principles of bet-hedging but by increasing the likelihood that multiple categories are in working memory at the time of the induction. We discuss implications for improving everyday inductions. (shrink)