This paper describes an approach to user adaptation realized in a multiagent interface system for interaction with a virtual environment. The interface agency adapts to users’ individual preferences by learning from direct feedback. The core idea is that agents that were successful in meeting the user’s expectations are given credit while unsuccessful agents are “discredited.” Communicating credit values, agents organize themselves so that the overall behavior of the interface agency gradually adapts to the individual user as the session is proceeding.
CITATION STYLE
Lenzmann, B. (1996). A user-adaptive interface agency for interaction with a virtual environment. In Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics) (Vol. 1042, pp. 141–151). Springer Verlag. https://doi.org/10.1007/3-540-60923-7_24
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