NDLI: An adaptive architecture for physical agents

Content Provider	IEEE Xplore Digital Library
Author	Langley, P.
Copyright Year	2005
Description	Author affiliation: Comput. Learning Lab., Stanford Univ., CA, USA (Langley, P.)
Abstract	In this paper we describe ICARUS, an adaptive architecture for intelligent physical agents. We contrast the framework's assumptions with those of earlier architectures, taking examples from an in-city driving task to illustrate our points. Key differences include primacy of perception and action over problem solving, separate memories for categories and skills, a hierarchical organization on both memories, strong correspondence between long-term and short-term structures, and cumulative learning of skill hierarchies. We support claims for ICARUS' generality by reporting our experience with driving and three other domains. In closing, we discuss limitations of the current architecture and propose extensions that would remedy them.
Sponsorship	IEEE Comput. Soc. Web Intelligence Consortium (WIC) Assoc. for Comput. Machinery (ACM)
Starting Page	18
Ending Page	25
File Size	240802
Page Count	8
File Format	PDF
ISBN	0769524168
DOI	10.1109/IAT.2005.36
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2005-09-19
Publisher Place	France
Access Restriction	Subscribed
Rights Holder	IEEE/CSP
Subject Keyword	Intelligent agent Computer architecture Intelligent systems Vehicle driving Physics computing Laboratories Computational intelligence Problem-solving Multiagent systems Protocols
Content Type	Text
Resource Type	Article

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4	Project PI / Joint PI	Principal Investigator and Joint Principal Investigators of the project	Dr. B. Sutradhar bsutra@ndl.gov.in Prof. Saswat Chakrabarti will be added soon
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