DocumentCode
2165583
Title
Asymmetry in learning automata playing multi-level games
Author
Billard, Edward A.
Author_Institution
Dept. of Math. & Comput. Sci., California State Univ., Hayward, CA, USA
Volume
3
fYear
1998
fDate
11-14 Oct 1998
Firstpage
2202
Abstract
To achieve synergy, it is important for agents to form cooperative groups such that shared resources, strategies and information can be fully utilized. A game-theoretic model is presented in which agents decide whether it is beneficial to form groups and what actions to take within the chosen context. Learning automata are used to model this multi-level decision-making process. The results show that asymmetries in initialization and equilibria do not effect this process. With delayed information, both symmetric and asymmetric penalties lead to chaos but with different Lyapunov exponents
Keywords
cooperative systems; distributed decision making; game theory; learning automata; Lyapunov exponents; agents; asymmetric penalties; asymmetries; chaos; cooperative groups; delayed information; game theory; learning automata; multi-level decision making process; multi-level games; symmetric penalties; Area measurement; Chaos; Computer science; Context modeling; Decision making; Delay; Game theory; Learning automata; Mathematics; Probability distribution;
fLanguage
English
Publisher
ieee
Conference_Titel
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location
San Diego, CA
ISSN
1062-922X
Print_ISBN
0-7803-4778-1
Type
conf
DOI
10.1109/ICSMC.1998.724982
Filename
724982
Link To Document