Evolutionary Learning in Agent-Based Combat Simulation
In this paper, we consider one of old-age problems about trade-off relation between homogeneity and diversity. We investigate combat based on agent-based simulation, not conventional mathematical model based on attrition. By introducing synthetic approach and adapting evolutionary learning to action rules that are expressed by a combination of parameters in combat simulation, we focus on the interaction between sets of action rules. For searching how many sets of action rules does work well, we change the number of sets of action rules. And we make statistical analysis and show that there is good intermediate stage between high homogeneity and high diversity in group.
KeywordsComplex Adaptive System Action Rule Evolutionary Learn Personality Parameter Fire Range
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