NDLI: How far can i reach? A case study in robot knowledge acquisition

Content Provider	IEEE Xplore Digital Library
Author	Kejun Wang Tongchun Du Xiaofei Yang Perlis, D. Shamwell, J.
Copyright Year	2014
Description	Author affiliation: Coll. of Autom., Harbin Eng. Univ., Harbin, China (Kejun Wang; Tongchun Du; Xiaofei Yang) \|\| Dept. of Comput. Sci., Univ. of Maryland, College Park, MD, USA (Perlis, D.; Shamwell, J.)
Abstract	This paper mainly describes robot knowledge acquisition and reasoning underlying actual applications, starting with introducing some basic problems with constructing an intelligent system. On one hand, growing neural gas (GNG) and Natural Actor-Critic (NAC) are used for acquiring source knowledge; Afterward on the other hand, active logic and metacognitive loop (MCL) are incorporated as reasoning engines/mechanisms and robot knowledge base (KB) is established for knowledge representation and reasoning. Several cases including “How far can I reach” are raised to support our arguments. Across these experiments and potential applications, we show that with suitable symbolic representation of knowledge and a well-designed systematic structure, our autonomous robot agent can basically perceive, learn from and interact with the environment, and reason about and handle unexpected problems using its knowledge base. Some analysis and future research directions are presented in the end.
Starting Page	1068
Ending Page	1072
File Size	245312
Page Count	5
File Format	PDF
ISBN	9781479939787
e-ISBN	9781479939794
DOI	10.1109/ICMA.2014.6885846
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	2014-08-03
Publisher Place	China
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Cognition Knowledge acquisition Robot sensing systems Educational institutions Engines knowledge representation & reasoning autonomous robots robot KB active logic MCL
Content Type	Text
Resource Type	Article

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