Learning to understand a single causal system can be an achievement, but humans must learn about multiple causal systems over the course of a lifetime. We present a hierarchical Bayesian framework that helps to explain how learning about several causal systems can accelerate learning about systems that are subsequently encountered. Given experience with a set of objects, our framework learns a causal model for each object and a causal schema that captures commonalities among these causal models. The schema organizes the (...) objects into categories and specifies the causal powers and characteristic features of these categories and the characteristic causal interactions between categories. A schema of this kind allows causal models for subsequent objects to be rapidly learned, and we explore this accelerated learning in four experiments. Our results confirm that humans learn rapidly about the causal powers of novel objects, and we show that our framework accounts better for our data than alternative models of causal learning. (shrink)

Varios enfoques teóricos y disciplinas se han comprometido con el problema de nuestra relación cognitiva con los animales (e incluso entre ellos). De qué forma lograr el mejor acercamiento es aún un tema controversial. En este trabajo, analizamos algunas de las posibilidades presentadas en los últimos años. Cuando el acceso cognitivo al psiquismo animal se realiza por vía naturalista, abierta a la psicología, una de las alternativas brindadas es la llamada Teoría de la Mente (ToM). La Teoría de la mente, (...) también conocida como lectura de la mente, mentalización o atribución de estados mentales, sería la capacidad de atribuir a otros sujetos estados mentales, como deseos y creencias, lo que supondría que el sujeto en cuestión dispone de algo así como una “teoría” de la mente del otro. En 2008 Call y Tomasello revisaron la pregunta que lanzó la investigación de ToM tres décadas antes: “¿Tiene el chimpancé una teoría de la mente?”. 10 años antes, había un consenso considerable de la literatura experimental de que la ToM sería una propiedad exclusiva de los humanos. Call y Tomasello concluyeron en 2008 que las cosas habían cambiado: varias tareas evidenciaron que los simios eran sensibles a las metas e intenciones que subyacen en las acciones de los demás simios. Para este enfoque, es crucial decidir si el comportamiento, que es una variable observable, es un fiel reflejo de lo que está pasando al nivel mental. Presentamos el simulacionismo como una alternativa a la ToM. La primera persona es la perspectiva desde la cual trabajan los simulacionistas, ya que a partir de los datos observacionales y actitudes que “el otro” aporta, pueden “ponerse en su sitio” para así, simular y comprender sus estados mentales. La ToM y el simulacionismo suelen caracterizarse dentro del mismo enfoque (teorías mentalistas). Sin embargo, los simulacionistas niegan la implicación de cualquier tipo de teorización, ya sea personal o subpersonal, al producirse el acceso cognitivo. Cuando el estudio de la mente se realiza mediante disciplinas científicas, psicología, neurociencias, etc., los métodos utilizados por las ciencias positivas deben enfrentarse al problema de la subdeterminación teórica por parte de la evidencia empírica. Tales limitaciones pueden ser sorteadas si nos acercamos al tema a través de la psicología animal o la fenomenología y no desde un enfoque que tome como modelo epistemológico principal a la física. Mostramos que los enfoques empáticos, y las perspectivas de segunda persona son ejemplos de este tipo de acercamiento. Debido al problema de la subdeterminación teórica, dado un conjunto finito de “hechos empíricos”, existen muchas teorías rivales que son corroboradas por tal conjunto. Esto implica que no podremos decidirnos por una de las teorías rivales contando sólo con el cuerpo evidencial en cuestión. El análisis de los casos presentados muestra que el problema de la subdeterminación teórica pocas veces es considerado por los científicos que tratan el comportamiento animal. Concluimos que las discusiones presentadas muestran una complejidad que invita a un acercamiento multidisciplinar, y que aún estamos lejos de llegar a un consejo general sobre la cuestión. (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)

In museum settings, caregivers support children's learning as they explore and interact with exhibits. Museums have developed exhibit design and facilitation strategies for promoting families' exploration and inquiry, but these strategies have rarely been contrasted. The goal of the current study was to investigate how prompts offered through staff facilitation vs. labels printed on exhibit components affected how family groups explored a circuit blocks exhibit, particularly whether children set and worked toward their own goals, and how caregivers were involved in (...) children's play. We compared whether children, their caregivers, or both set goals as they played together, and the actions they each took to connect the circuits. We found little difference in how families set goals between the two conditions, but did find significant differences in caregivers' actions, with caregivers in the facilitation condition making fewer actions to connect circuits while using the exhibit, compared to caregivers in the exhibit labels condition. The findings suggest that facilitated and written prompts shape the quality of caregiver-child interactions in distinct ways. (shrink)