DocumentCode
2462580
Title
Generation of Unconstrained Looping Programs for Control of Xpilot Agents
Author
Parker, Gary B. ; Doherty, Timothy S. ; Parker, Matt
Author_Institution
Connecticut Coll., Vancouver
fYear
0
fDate
0-0 0
Firstpage
1216
Lastpage
1223
Abstract
An unconstrained cyclic genetic algorithm (CGA) is presented as a means to evolve multi-loop behavior for an autonomous agent. The evolved programs control autonomous agents in the network space combat game Xpilot. Ultimately, the agent´s goal is survival; it must learn to move within a restricted area, avoiding obstacles while engaged in combat with an opposing agent. The CGA learned multi-loop control programs that significantly improved the agent´s survivability in the hostile Xpilot environment.
Keywords
collision avoidance; genetic algorithms; mobile robots; reliability; telerobotics; Xpilot agents; autonomous agent; multiloop control programs; network space combat game; obstacle avoidance; survivability; unconstrained cyclic genetic algorithm; unconstrained looping programs; Autonomous agents; Control system synthesis; Control systems; Evolutionary computation; Game theory; Genetic algorithms; Navigation; Orbital robotics; Robot control; Switches;
fLanguage
English
Publisher
ieee
Conference_Titel
Evolutionary Computation, 2006. CEC 2006. IEEE Congress on
Conference_Location
Vancouver, BC
Print_ISBN
0-7803-9487-9
Type
conf
DOI
10.1109/CEC.2006.1688448
Filename
1688448
Link To Document