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Title:

Path-finding Using Reinforcement Learning and Affective States

Document type:
Konferenzbeitrag
Contribution type:
Poster
Author(s):
Feldmaier, Johannes; Diepold, Klaus
Pages contribution:
543 - 548
Abstract:
During decision making and acting in the environment humans appraise decisions and observations with feelings and emotions. In this paper we propose a framework to incorporate an emotional model into the decision making process of a machine learning agent. We use a hierarchical structure to combine reinforcement learning with a dimensional emotional model. The dimensional model calculates two dimensions representing the actual affective state of the autonomous agent. For the evaluation of this c...     »
Dewey Decimal Classification:
620 Ingenieurwissenschaften
Editor:
IEEE
Book / Congress title:
The 23rd IEEE International Symposium on Robot and Human Interactive Communication
Date of congress:
25-29 Aug. 2014
Year:
2014
Month:
Aug
Pages:
6
Fulltext / DOI:
doi:10.1109/ROMAN.2014.6926309
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