Cognitive modeling with context sensitive reinforcement learning
(2004) p.10-19- Abstract
- We describe how a standard reinforcement learning algorithm can be changed to include a second contextual input that is used to modulate the learning in the original algorithm. The new algorithm takes the context into account during relearning when the previously learned actions are no longer valid. The algorithm was tested on a number of cognitive experiment and shown to reproduce the learning in both a task switching test and in the Wisconsin Card Sorting Test. In addition, the algorithm was able to learn a context sensitive categorization of objects in the Labov experiment.
Please use this url to cite or link to this publication:
https://lup.lub.lu.se/record/531323
- author
- Balkenius, Christian LU and Winberg, Stefan LU
- organization
- publishing date
- 2004
- type
- Chapter in Book/Report/Conference proceeding
- publication status
- published
- subject
- host publication
- Proceedings of AILS 04 ( Report / Lund Institute of Technology, Lund University ; 151)
- editor
- Malek, J.
- pages
- 10 - 19
- publisher
- Department of Computer Science, Lund University
- ISSN
- 1650-1276
- project
- Ikaros: An infrastructure for system level modelling of the brain
- language
- English
- LU publication?
- yes
- id
- cf0bf903-7770-4e51-993e-bc20240ac643 (old id 531323)
- alternative location
- http://www.lucs.lu.se/People/Christian.Balkenius/PDF/Balkenius.Winberg.2004.pdf
- date added to LUP
- 2016-04-01 16:49:42
- date last changed
- 2019-09-06 02:18:09
@inproceedings{cf0bf903-7770-4e51-993e-bc20240ac643, abstract = {{We describe how a standard reinforcement learning algorithm can be changed to include a second contextual input that is used to modulate the learning in the original algorithm. The new algorithm takes the context into account during relearning when the previously learned actions are no longer valid. The algorithm was tested on a number of cognitive experiment and shown to reproduce the learning in both a task switching test and in the Wisconsin Card Sorting Test. In addition, the algorithm was able to learn a context sensitive categorization of objects in the Labov experiment.}}, author = {{Balkenius, Christian and Winberg, Stefan}}, booktitle = {{Proceedings of AILS 04 ( Report / Lund Institute of Technology, Lund University ; 151)}}, editor = {{Malek, J.}}, issn = {{1650-1276}}, language = {{eng}}, pages = {{10--19}}, publisher = {{Department of Computer Science, Lund University}}, title = {{Cognitive modeling with context sensitive reinforcement learning}}, url = {{https://lup.lub.lu.se/search/files/4792451/624999.pdf}}, year = {{2004}}, }