Research On Knowledge Representation Language And Its Supporting Tool In Multi-agent Based Decision Simulation

By using the autonomy, intelligence and collaboration of Agent, the multi-agentdecision simulation can achieve effective simulation of decision-thinking anddecision-flow, which is an important method of researching decision action. And theknowledge representation problem in decision simulation system influences decisionsimulation results as the key factor. Now, how to effectively represent and usesimulation knowledge to adapt the changing decision field and simulation environmentis an important research issue.The paper presents the MDKSRL (Knowledge Representation Language inMulti-Agent Based Decision Simulation) and its supporting tool in order to solve theknowledge representation of multi-agent. First, the paper introduces the multi-agentdecision simulation framework model and analyzes the knowledge. Then, the paperfocuses on the design principle and operation mechanism of MDSKRL, including thegeneral design of the language, detailed definitions of the language and therepresentation, storage and use of knowledge. And the paper designs the supporting tool,which implements editing, analyzing and explaining the knowledge.Finally, MDSKRL and the supporting tool are applied to a multi-agent decisionsimulation system. Through the experiment, the paper proves the feasibility ofMDSKRL and the supporting tool, also verifies MDSKL is scalable and the knowledgedynamic update mechanism is effective.