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
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;
Conference_Titel :
Systems, Man, and Cybernetics, 1998. 1998 IEEE International Conference on
Conference_Location :
San Diego, CA
Print_ISBN :
0-7803-4778-1
DOI :
10.1109/ICSMC.1998.724982