SUBJECT
Informatics
CCNM17-104
seminar
Master
4
Semester 1
Autumn semester
Introduction to cognitive informatics
- What is computational cognitive modelling, types of cognitive modelling, what is computational cognitive modelling good for, multiple levels of cognitive modelling, successes and pitfalls of cognitive modelling
- Introduction to symbolic modelling
- Introduction to connectionist type modelling
- Connectionist vs Symbolic vs Hybrid Modelling
Connectionist Modelling
- What is an artificial neuron and how it transmits information – Activation functions, connection weights, output computation
- McCulloch-Pitts neuronal type
- Learning rules
- Network behaviour
- Worked examples
Learning and memory and knowledge representation, concepts, categories
- Psychological studies and computational models of concept formation, concept learning and knowledge representation
Symbolic Modelling (Systems and Architectures)
- ACT-R
- Soar
- CLARION
Learning outcome, competences knowledge:
- understanding computational cognitive modelling
- has an overall view of the field of informatics
attitude:
- is capable of cooperation and solving tasks in teams;
skills: - is able to see causal relationships, can think logically, and can prepare comprehensive reviews;
Learning activities, learning methods:
Lectures and interactive discussions
Course textbook:
Polk, T. A., & Seifert, C. M. (2002). Cognitive Modelling. Cambridge, Mass.: MIT Press.
(http://api.ning.com/files/pFUGNH4chIZY4rfEDP1DSg- pM7eUjJOa- wYjcjvSp0xyhMqBucXw37KXqOPz6xkymUfvtqMbaeF3dMEmJHkR5dSTzcjWP2PS/CognitiveModelingBradfordBooks.pdf)
Suggested Readings:
- Sun, R. (2008). Introduction to computational cognitive modeling. In: R. Sun (Ed.), The Cambridge Handbook of Computational Psychology (pp.3-19). New York: Cambridge University Press. (http://www.cogsci.rpi.edu/~rsun/folder-files/sun-CHCP-intro.pdf)
- Sun, R. (2001). Artificial intelligence: Connectionist and symbolic approaches. In: N. J. Smelser, & P. B. Baltes (Eds.), International Encyclopedia of the Social and Behavioral Sciences (pp.783-789). Oxford: Pergamon/Elsevier. (http://www.cogsci.rpi.edu/~rsun/sun.encyc01.pdf)
- Plautt, D. C. (1999). Connectionist modeling. In A. Kasdin (Ed.), Encyclopedia of Psychology. Washington DC: Americal Psychological Association. (http://www.cnbc.cmu.edu/~plaut/papers/pdf/Plaut00chap.conn.pdf)
- Stufflebeam, R. (2006). Connectionism: An introduction. Retrieved from http://www.mind.ilstu.edu/curriculum/connectionism_intro/connectionism_1.php? modGUI=76&compGUI=1928&itemGUI=3343
- Marsalli, M. (n.d.). McCulloch-Pitts neurons. Retrieved from http://www.mind.ilstu.edu/curriculum/modOverview.php?modGUI=212
- Hinton, G. (2002). How Neural Networks Learn from Experience. In: T. A. Polk, & C. M. Seifert. Cognitive Modelling (pp. 181-197). Cambridge, Mass.: MIT Press.
- Concept Learning. (2014). In Wikipedia. Retrieved from http://en.wikipedia.org/wiki/Concept_learning
- Semantic network. (2014). In Wikipedia. Retrieved from http://en.wikipedia.org/wiki/Semantic_network
- Sowa, J. F. (1992). Semantic networks. In: S. C. Shapiro (Ed.). The Encyclopedia of Artificial Intelligence (pp. ) New York: Wiley. (http://www.jfsowa.com/pubs/semnet.htm)
- Rogers, T. T., & McClelland, J. L. (2003). Categories, hierarchies and theories. In: T. T. Rogers & J. L. McClelland. Semantic Cognition: A Parallel Distributed Processing Approach (pp. 1-26). Cambridge, MA: MIT Press.
http://nwkpsych.rutgers.edu/~jose/courses/578_mem_learn/2012/readings/Rogers_McClelland_2003.pdf) - Rogers, T. T., & McClelland, J. L. (2003 A PDP Theory of Semantic Cognition. In: T. T. Rogers & J. L. McClelland. Semantic Cognition: A Parallel Distributed Processing Approach (pp. 27-44). Cambridge, MA: MIT Press.
http://nwkpsych.rutgers.edu/~jose/courses/578_mem_learn/2012/readings/Rogers_McClelland_2003.pdf) - Prince, A., & Smolensky, P. (2002). Adaptive Resonance Theory. In: T. A. Polk, & C. M. Seifert. Cognitive Modelling (pp. 289-316). Cambridge, Mass.: MIT Press.
- Anderson, J. R. (2002). ACT: A Simple Theory of Complex Cognition. In: T. A. Polk, & C. M. Seifert. Cognitive Modelling (pp. 49-70). Cambridge, Mass.: MIT Press.
- Lehman, J. F., Laird, J., & Rosenbloom, P. (2006). A gentle introduction to Soar: An architecture for human cognition. Retrieved from http://ai.eecs.umich.edu/soar/sitemaker/docs/misc/GentleIntroduction-2006.pdf
- Allison, R. (n.d.). A short tutorial on CLARION. Retrieved from http://www.cogsci.rpi.edu/~rsun/ra-tutorial.pdf