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A compact multiagent optimization system (MAOS C ) based on autonomy oriented computing (AOC) is presented. Performed by a society of autonomous entities in iterative cycles, an optimization algorithm can simply be described by a macro generate-and-test behavior, which deploys a few elemental generating behaviors under conditioned reflex behaviors supported by a testing operation library. MAOS C provides a simple framework for not only realizing and comparing algorithms, but also deployingdoi:10.1109/iat.2005.6 dblp:conf/iat/XieL05 fatcat:c25czpobevgdnnv2d7jbdyukpy