NDLI: Planning with a functional neural network architecture

Content Provider	IEEE Xplore Digital Library
Author	Panagiotopoulos, D.A. Newcomb, R.W. Singh, S.K.
Copyright Year	1990
Abstract	Introduces the concept of planning in an interactive environment between two systems: the challenger and the responder. The responder's task is to produce behavior that relates to the challenger's behavior through some response function. In this setup, we concentrate planning on the responder's actions and use the produced plan in order to control the responder. In general, the responder is assumed to be a nonlinear system whose input-output (I/O) map may be expressed by a Volterra series. The planner uses an estimate of the challenger's future output sequence, the response function, and a model of the responder's I/O relation implemented through a functional artificial neural network (FANN) architecture, in order to produce the input sequence that will be applied to the responder in the future, in parallel-time with the challenger's corresponding output sequence. The responder accepts input from the planner, which may be combined with feedback information, in order to produce an output sequence that relates to the challenger's output sequence according to the response function. The importance of planning for the generation of smooth behavior is discussed, and the effectiveness of the planner's implementation using neural network technology is demonstrated with an example.
Sponsorship	IEEE Computational Intelligence Society
Starting Page	115
Ending Page	127
Page Count	13
File Size	581848
File Format	PDF
ISSN	10459227
Volume Number	10
Issue Number	1
Language	English
Publisher	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date	1999-01-01
Publisher Place	U.S.A.
Access Restriction	Subscribed
Rights Holder	Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword	Control systems Path planning Nonlinear systems Neural networks Process planning Robotics and automation Navigation Artificial neural networks Output feedback Neurofeedback
Content Type	Text
Resource Type	Article
Subject	Artificial Intelligence Computer Networks and Communications Computer Science Applications Software

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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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