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The Dynamics of Associative Learning in an Evolved Situated Agent
Artificial agents controlled by dynamic recurrent node net- works with fixed weights are evolved to search for food and associate it with one of two different temperatures depending on experience. The task requires either instrumental or classical conditioned responses to be learned. The paper extends previous work in this area by requiring that a situated agent be capable of re-learning during its lifetime. We anal- yse the best-evolved agents behaviour and explain in some depth how it arises from the dynamics of the coupled agent-environment system.
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Publication status
- Published
Publisher
Springer-VerlagPages
365.0Presentation Type
- paper
Event name
Proceedings of European Conference on Artificial Life, 2007Event location
LisbonEvent type
conferenceISBN
978-3-540-74912-7Department affiliated with
- Informatics Publications
Full text available
- No
Peer reviewed?
- Yes
Legacy Posted Date
2012-02-06Usage metrics
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