|Module lecturer||prof. UAM dr hab. Mariusz Urbański, mgr Andrzej Gajda|
|Lecturer position||Professor, adiunkt|
|Faculty||Faculty of Psychology and Cognitive Science|
Module aim (aims)
The course is aimed at deepening participants’ insights into contemporary theory and practice of logical analysis of reasoning and inference. On the theoretical side, we shall examine some models of logical analysis of reasoning, like syllogistics, logic of questions, abduction, and their applications in research on human cognition. On the practical side, we shall go in-depth into various ways of modeling abductive reasoning, both symbolic and connectionist, to study strengths and weaknesses of different formal methods vis-´a-vis real reasoning processes.
Pre-requisites in terms of knowledge, skills and social competences (where relevant)
Working knowledge of syntax, semantics and metalogic of classical logic, propositional modal alethic logics, three-valued logics and classical syllogistics. General knowledge of Artificial Neural Networks. English at B2 level.
Week 1: Reasoning: what is it?
Week 2: Reasoning with quantifiers: syllogistics
Week 3: Reasoning with questions: Inferential Erotetic Logic
Week 4: Reasoning with uncertainty: Abduction.
Week 5: Abductive Question-Answer System for CPL
Week 6: Neural-symbolic system, I
Week 7: Neural-symbolic system, II
Week 8: Abductive Logic Programming
Week 9: Individual appointments (term paper consultations)
Week 10: Individual appointments (term paper consultations)
Week 11: Individual appointments (term paper consultations)
Week 12: Individual appointments (term paper consultations)
Week 13: Individual appointments (term paper consultations)
Week 14: Individual appointments (term paper consultations)
Week 15: Individual appointments (term paper vivas)
K. Stenning and M. van Lambalgen, Human Reasoning and Cognitive Science The MIT Press, 2008.
J. E. Adler and L. Rips (eds.) Reasoning. Studies of Human Inference and Its Foundations., Cambridge UP, 2008.
L. Magnani and T. Bertolotti (eds.) Springer Handbook of Model-Based Science, Springer, 2017.
A. Wiśniewski, Questions, Inferences, and Scenarios, College Publications, 2013.
A. S. d’Avila Garcez, K. Broda, and D. M. Gabbay, Neural-Symbolic Learning Systems: Foundations and Applications. Springer-Verlag 2002.