Research And Application On Multi-agent System Modeling, Learning And Cooperation

In the past few years, most of the research of DAI (Distributed Artificial Intelligence) focused on Agent and Multi-agent System theory. In this dissertation, detailed study was made on Agent technology from knowledge denotation, modeling, Agent learning to multi-agent cooperation. Improvements were made on the basis of early research, as well as new opinions and applications were proposed.This dissertation is composed of follows:a) Introducing new logic operator into the traditional Agent BDI model, including BEL, ASM, DES, GOAL and INT, in order to describe the dynamic restrictions and interactive triggering relations between BELIEF, DESIRE and INTENTION of Agent. A new intentional model was built in complementation of the KD45 regular modal logic axiom, which is the base of Agent self-control interaction with the outer environment.b) Deducing is an important property of Agent intelligence. Symbol logic method is unable to guarantee the complement of knowledge description, which leads to complicated deducing process. We introduce Fuzzy Cognitive Map into Agent modeling and deducing, substitute symbolic description and inference with simple mathematical computing, achieving Agent intelligent decision-making in complex environment.c) Learning ability is the base of Agent self-determination behavior. Reinforcement Learning is an applicable machine learning method of Agent state and knowledge. We combined RL and fuzzy logic together to make improvement on Agent inner model and state denotation method. This Fuzzy Reinforcement Learning Method decreases the requirement of modeling precision and makes the algorithm more applicable.d) On the research of Agent cooperation, on the basis of Contract Net Model,we define relationship weights between the network nodes. By means of pre-classification of the agents in a system, agents negotiation and task distribution are handled in less time and resource consumption, the whole system performance are greatly improved.e) Application of Agent technology are also studied in many fields such as system optimization, transportation schedule and decision support system, ect.