Agent behavior and agent models in unregulated markets

Mobile-agent systems show significant promise as the most effective way to harness the power of the Internet and the massive collection of information and opportunity that the Internet holds. However the efficient organization and control of these systems remains one of a number of unsolved problems with this approach to network computing. This paper examines a mobile-agent system with specific focus on environment sensing, preemptive load balancing and open agent markets. Agent behaviour is studied with actual agent systems using progressively sophisticated agent migration strategies.It is shown that actual modeling shows interesting and difficult to predict behaviour in the agent systems. It is shown that mobile agents with relatively simple migration strategies can cause loads in self-regulating agent markets to oscillate. It is further shown that using Autoregressive modeling to predict the market behaviour can allow individual agents to significantly outperform other agents. However the fidelity of the model is critical to the success of the agents. The criticality of good agent strategies and actual agent system modeling is thus highlighted.