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Journal Articles Applied Artificial Intelligence Year : 2005

Analysis and Synthesis of Learning Agent's Communicative Behavior

Abstract

This paper is about people. It is about understanding how learning and communication mutually influence one another, allowing people to infer each other's communicative behavior. In order to understand how people learn to communicate, we refer to existing theories. They are the logical theories of learning and communication, situated cognition, and activity theory. Thus, this paper is about applying existing theories of analyzing conversations, human learning, and memory to a range of scenarios of actual human conversations. It also introduces a new way of analyzing conversations. We have recorded and observed actual human communications on the Web. We have applied those theories to analyze these communication scenarios. We describe the preliminary results on the analyses of the communication scenarios. In particular, we show our analysis of the recorded conversational structures. We illustrate how the re-enacting and re-sequencing of conversational structures is adapted to the context (i.e., environment) moment by moment. From our analyses, we found that people have internal rules (e.g., a combinatorial rule system). These internal rules can be related to how a person learns, adapts, and merges protocols situated in their context of communication. Our long term goal is to make use of these analyses to improve human communication on the Grid.

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Dates and versions

lirmm-00105303 , version 1 (11-10-2006)

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Nik Nailah Binti Abdullah, Stefano A. Cerri. Analysis and Synthesis of Learning Agent's Communicative Behavior. Applied Artificial Intelligence, 2005, 19 (9-10), pp.1015-1041. ⟨10.1080/08839510500304116⟩. ⟨lirmm-00105303⟩
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