The sequential logic model to solve the multi-Agent dynamic cooperative tasks of complex self-adaptive system.

Solving dynamic complex problem is difficult in the theory and applied research of artificial intelligence and complex adaptive systems. Idea from histology is that the auto-run unit in self-adaptive system is abstracted to be Agent, the complex adaptive system is considered as a multi-Agent tissue. The behavior of complex dynamic systems in time and space is described. The adaptive mechanisms and structure model of solving multi-Agent dynamic cooperative tasks based on sequential active logic are proposed. The production process and realization of BDI belief, desire, intention of solving task are analyzed. The semantic rules and action rules of cooperative deduction is builded. The selection algorithm of cooperative groups is given. From the mind change of task solving Agent, the paper describes the six stages to realize the solving model of dynamic cooperative tasks. The six stages are dynamic allocation of tasks, collaboration will produce, generate collaborative groups, common planning making, collaborative groups action and evaluation of results. Experiments and simulation on MAGE and other platforms prove the feasibility and effectiveness of our proposed approaches. [ABSTRACT FROM AUTHOR]