Authors:
Sungsoo Lim
;
Keunhyun Oh
and
Sung-bae Cho
Affiliation:
Yonsei University, Korea, Republic of
Keyword(s):
Mixed-initiative interaction, Global workspace, Semantic network, Spreading activation theory.
Related
Ontology
Subjects/Areas/Topics:
Applications
;
Artificial Intelligence
;
Cognitive Systems
;
Computational Intelligence
;
Evolutionary Computing
;
Knowledge Engineering and Ontology Development
;
Knowledge-Based Systems
;
Natural Language Processing
;
Pattern Recognition
;
Soft Computing
;
Symbolic Systems
Abstract:
Mixed-initiative interaction (MII) plays an important role in conversation agent. In the former MII research, MII process only static conversation and cannot change the conversation topic dynamically by the system because the agent depends only on the working memory and predefined methodology. In this paper, we propose the mixed-initiative interaction based on human cognitive architecture and memory structure. Based on the global workspace theory, one of the cognitive architecture models, proposed method can change the topic of conversation dynamically according to the long term memory which contains past conversation. We represent the long term memory using semantic network which is a popular representation for storing knowledge in the field of cognitive science, and retrieve the semantic network according to the spreading activation theory which has been proven to be efficient for inferring in semantic networks. Through some dialogue examples, we show the usability of the proposed
method.
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