Modeling emotions and reason in agent-based systems.

Oliveira, Fernando S.

Abstract

We analyze how to develop an agent-based system in which agents evolve co-evolutionary endogenous rules of behavior by using best response and emotions. We show that best response is not sufficient to define complete and consistent rules of behavior and we prove that the use of emotions, which complement reason, is necessary to learn rules of behavior. We model four different emotions (apathy, patience, anger and confidence) which enable the agent to deal with the rewards and with others. We propose an algorithm to model automata-based systems incorporating rationality and emotions.

Citation

OLIVEIRA, F.S. 2010. Modeling emotions and reason in agent-based systems. Computational economics [online], 35(2), pages 155-164. Available from: https://doi.org/10.1007/s10614-009-9188-0

• Journal Article Type: Article
• Acceptance Date: Sep 9, 2009
• Online Publication Date: Sep 24, 2009
• Publication Date: Feb 28, 2010
• Deposit Date: Oct 21, 2023
• Publicly Available Date: Nov 15, 2023
• Journal: Computational economics
• Print ISSN: 0927-7099
• Electronic ISSN: 1572-9974
• Publisher: Springer
• Peer Reviewed: Peer Reviewed
• Volume: 35
• Issue: 2
• Pages: 155-164
• DOI: https://doi.org/10.1007/s10614-009-9188-0
• Keywords: Artificial intelligence; Machine learning; Emotions; Agent-based models
• Public URL: https://rgu-repository.worktribe.com/output/2114783