Close-in weapon system planning based on multi-living agent theory

The close-in weapon system(CIWS)is a combat system that faces a complex environment full of dynamic and unknown challenges,whose construction and planning require a systematic design method.Multiliving agent(MLA)theory is a methodology for the combat system design,which uses the livelihood degree to evaluate the multi-dimensional long-term operational effectiveness of the system;whereas,there is still no uniform quantization framework for the livelihood degree,and the adjustment methods of livelihood degree need to be further improved.In this paper,we propose the uniform quantization framework for the livelihood degree and detailed discuss the methods of livelihood adjustment.Based on the MLA theory,the multi-dimensional operational effectiveness of the missile-gun integrated weapon system(MGIWS)is analyzed,and the long-term combat effectiveness against the saturation attack is assessed.Furthermore,the planning problem of the equipment deployment and configuration is investigated.Two objectives,including the overall livelihood degree and cost-effectiveness(CE),are proposed,and the optimization method based on genetic algorithm(GA)is studied for the planning problem.

AUTONOMOUS AGENT FRAMEWORK AND ITS DECISION-MAKING

Autonomy, a key property associated with the agent, is an important topic in the current research of the agent theory. Although no definition of the agent autonomy is universally accepted, an important aspect of the agent autonomy is the decision-making capability of the agents. This paper investigates the autonomy of the agent, presents a framework for autonomous agent and discusses its decision-making process. Started with introducing a language for representing autonomous agent, a framework is proposed for modeling autonomous agent based on a BDI model and the situation calculus. Finally, a kind of decision-making process of the autonomous agent is presented.

Optimization of Structure of Agricultural Insurance Subsidies:A Multi-task Principal Agent Model

Optimizing the structure of agricultural insurance subsidies is of great significance to increasing the supply of agricultural insurance and strengthening the effects of agricultural insurance policies.This paper optimized the structure of agricultural insurance subsidies.It decomposed insurance activities into three parts:underwriting,claim settlement,and agricultural services.Next,it incorporated adverse selection risks,moral hazards,agricultural production and operation risks,insurance company's behavioral decisions and its risk attitudes into the multi-task principal agent analysis framework.Finally,it discussed how the government designs a subsidy mechanism and adjusts the subsidy structure to increase the insurance supply.

Differentiating and Subdividing for Concept of Earnings Management

Through discriminating the concept of unreal accounting information and differentiating earnings management and profit manipulation, the paper ascertains the concept of earnings management by applying the theories of agent, game and information transfer etc., and then subdivides its content.