Simulation and Analysis of Adaptive Agents: an Integrative Modelling Approach

Agent-based simulation methods are a relatively new way to address complex systems. Usually, the idea is that the agents used are rather simple, and the complexity and adaptivity of such a system are modeled by the interaction between these agents. How-ever, another way to exploit agent-based simulation methods is by use of agents that themselves also have certain forms of learning or adaptation. In order to simulate adap-tive agents with abilities matching those of their real-world biological or societal coun-terparts, a natural approach is to incorporate certain adaptation mechanisms such as classical conditioning into agent models. Existing models for adaptation mechanisms are usually based on quantitative, numerical methods, and in particular, differential equa-tions. Since agent-based simulation is usually based on qualitative, logical languages, these quantitative models are often not directly appropriate as an input in the con-text of agent-based simulation. To deal with this problem, this paper puts forward an integrative approach to simulate and analyze the dynamics of complex systems, in par-ticular a conditioning process of an adaptive agent, integrating quantitative, numerical and qualitative, logical aspects within one expressive temporal specification language. T