DocumentCode :
1680081
Title :
Learning in traffic control: adaptive processes and EAMs
Author :
Selfridge, Oliver G. ; Feurzeig, Wally
Volume :
3
fYear :
2002
fDate :
6/24/1905 12:00:00 AM
Firstpage :
2598
Lastpage :
2603
Abstract :
The fundamentals of our approach are that every action undertaken by a (sub)agent is an act of control; and hence is contained in an adaptive loop. We present a number of elementary adaptive modules (EAMs), the basic building blocks of adaptive agent systems, with a discussion of their use, their control, and their behaviors under different conditions; we also discuss the host of problems that we expect to run into. We apply these ideas to a model of traffic control by agents that run vehicles and control traffic lights
Keywords :
adaptive control; adaptive systems; intelligent control; learning systems; multi-agent systems; road vehicles; traffic control; adaptive agent systems; adaptive loop; adaptive processes; elementary adaptive modules; traffic control; traffic lights; Adaptive control; Adaptive systems; Algorithms; Artificial intelligence; Control systems; Humans; Intelligent agent; Machine learning; Programmable control; Traffic control;
fLanguage :
English
Publisher :
ieee
Conference_Titel :
Neural Networks, 2002. IJCNN '02. Proceedings of the 2002 International Joint Conference on
Conference_Location :
Honolulu, HI
ISSN :
1098-7576
Print_ISBN :
0-7803-7278-6
Type :
conf
DOI :
10.1109/IJCNN.2002.1007553
Filename :
1007553
Link To Document :
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