The aim of teleosemantics is to give a scientifically respectable, or ‘naturalistic’ theory of mental content. In the debates surrounding the scope and merits of teleosemantics a lot has been said about the concept of indication (or carrying information). The aim of this paper is to focus on the other key concept of teleosemantics: biological function. It has been universally accepted in the teleosemantics literature that the account of biological function one should use to flesh out teleosemantics is that of (...) etiological function. My claim is that if we replace this concept of function with an alternative one (that we have independent reasons to accept) and if we also restrict the scope of teleosemantics, we can arrive at an account of biologizing mental content that is much less problematic than the previous attempts. (shrink)

In recent years, developmental psychologists have increasingly been interested in various forms of prosocial behavior observed in infants and young children—in particular comforting, sharing, pointing to provide information, and spontaneous instrumental helping. We briefly review several models that have been proposed to explain the psychological mechanisms underpinning these behaviors. Focusing on spontaneous instrumental helping, we home in on models based upon what Paulus :77–81, 2014) has dubbed ‘goal-alignment’, i.e. the idea that the identification of an agent’s goal leads infants to (...) take up that goal as their own. We identify a problem with the most well-known model based upon this idea, namely the ‘goal contagion’ model. The problem arises from the way in which the model specifies the content of the goal which is identified and taken up. We then propose an alternative way of specifying the content of the goal, and use this as a starting point for articulating an alternative model based upon the idea of alignment, namely the ‘goal slippage’ model. By elucidating the difference between goal contagion and goal slippage, we contribute to the articulation of experimental criteria for assessing whether and when the mechanisms specified by these two models are at work. (shrink)

In this paper, we address reports of “selfless” experiences from the perspective of active inference and predictive processing. Our argument builds upon grounding self-modelling in active inference as action planning and precision control within deep generative models – thus establishing a link between computational mechanisms and phenomenal selfhood. We propose that “selfless” experiences can be interpreted as cases in which normally congruent processes of computational and phenomenal self-modelling diverge in an otherwise conscious system. We discuss two potential mechanisms – within (...) the Bayesian mechanics of active inference – that could lead to such a divergence by attenuating the experience of selfhood: “self-flattening” via reduction in the depth of active inference and “self-attenuation” via reduction of the expected precision of self-evidence. (shrink)

In this work I argue that emotion plays a key role in ensuring a unified perspective on the world. In particular, while many thoughts and feelings surface onto consciousness, it is not clear how they get combined into a unified point of view or what’s it’s like to be you at any given time. While many philosophers argue that reason or higher-order cognition plays a key role in delineating our point of view, I argue that higher-order cognition plays a subsidiary (...) role to lower-level emotion in delineating a unified perspective on the world. That is, empirical findings reveal that affect functions akin to attention in organizing our conscious experience and dictating what is actionable. As a result, split-brain patients (patients who have suffered losses to the unity of their higher-order cognition but retain undamaged emotional centers in the brain) manage to retain a unified phenomenal and agential perspective on the world. (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)