Stability Research Of Multi-agent System And Its Applications On Artificial Stock Market

The complex systems are one of the most challenging directions in recent years. Multi-agent system, which is a typical complex system, is gradually attracting more attention. Based on the National Natural Science Foundation of China, program for Liaoning Innovative Research Team in University and Liaoning Excellent Talents in University, stability of multi-agent system and its applications on artificial stock market is studied.Based on Liapunov stability theory, the dynamic and stability of multi-agent system is discussed. As multi-agent system's applications, the control and stability for multi-agent system is considered.The main contributions in this thesis are in four aspects:1. A stochastic multi-agent model is proposed, and Liapunvo stability theory is applied to study the center movement, exponent stability and convergence of the proposed stochastic model. Practical stability of a multi-agents system is discussed with different oscillations and necessary conditions are given for practical stability. A control rule for two orders multi-agent model is proposed to coordinated control, and the movement and stability of the model is studied on the based on the Laplace figure theory.2. The stability of multi-agent system is studied by adding some special agents, called 'control agents', which can change movement, but keep the basic local rule of the existing agents in the system. Special rules are applied for two kinds of multi-agents systems. Particle swarm optimization is applied to optimize the number of'control agents'. It's obviously that convergence rate is faster through adding properly more'control agents'. Moreover, divide of multi-agents system is studied by adding several'control agents'.3. Based on stability theory in multi-agent system, stability in artificial stock market (ASM) is studied. Firstly, expected price model, which is relational to SantaFe artificial stock market, is generated by simple attraction/rejection function. The price stability of model is discussed. Secondly, a new ASM including five populations is proposed. Different rules are applied for five populations, which will produce different price dynamic. Further more, a new clearing mechanism is offered by simulating real stock market.4. Based on'control agents'theory, the control and stability in artificial stock market model is discussed. It's different from the traditional stability theory in stock market. It's important to add the'control agents', who make decision by special trading rules to change the proportion of the orders, which can control fluctuation of the stock price and stability the finance market.