Title:
Anticipatory and Improvisational Robot via Recollection and Exploitation of Episodic Memories

dc.contributor.author Endo, Yoichiro
dc.date.accessioned 2006-03-14T17:27:35Z
dc.date.available 2006-03-14T17:27:35Z
dc.date.issued 2005
dc.description.abstract Previously, we have introduced an anticipatory robot that could generate a cognitive map while simultaneously localizing itself relative to it. Inspired by recent hippocampal researches, there, we demonstrated that the robot could exhibit anticipatory behavior if episodic memories that encode both spatial/nonspatial stimuli and behavioral actions are adequately utilized. In this paper, we will propose various ways to improve the previous method. For example, to address the computational complexity problem observed in the previous method, we will incorporate a new internal state variable inspired by the /somatic marker/ hypothesis (a biological premise that speculates the role of emotional responses in our brain in terms of memory and decision making). Furthermore, we conjecture that this framework for anticipation can be even extended farther for a robot to deal with a novel situation (i.e., improvisation). We will discuss the concept of our improvisational robot in terms of anticipatory failures and their possible solutions. en
dc.format.extent 180287 bytes
dc.format.mimetype application/pdf
dc.identifier.uri http://hdl.handle.net/1853/8351
dc.language.iso en_US en
dc.publisher Georgia Institute of Technology en
dc.relation.ispartofseries GVU Technical Report;GIT-GVU-05-15 en
dc.subject Anticipatory robot en
dc.subject Improvisational robot en
dc.subject Episodic memory en
dc.subject Somatic marker en
dc.subject Cognitive map en
dc.title Anticipatory and Improvisational Robot via Recollection and Exploitation of Episodic Memories en
dc.type Text
dc.type.genre Technical Report
dspace.entity.type Publication
local.contributor.corporatename GVU Center
local.relation.ispartofseries GVU Technical Report Series
relation.isOrgUnitOfPublication d5666874-cf8d-45f6-8017-3781c955500f
relation.isSeriesOfPublication a13d1649-8f8b-4a59-9dec-d602fa26bc32
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