Improving the representation of cognitive agents in agent-based modelling and simulation
Many agent based simulations need to represent humans, their behaviour and their decision making. Although animals can often be modelled well by simple reactive rules based on environment state, this is often inadequate for modelling human behaviours. The Belief Desire Intention (BDI) framework is a well developed theoretical and computational framework that is widely used in developing intelligent agent systems. Applications are developed by programming interacting agents with goals and plans, to provide a system which does some complex task (e.g. co-ordinating an electronic marketplace or logistics management for a large delivery company), typically in a dynamic environment. The execution engine of such systems then coordinates each agent's selection of plans and goals, depending on the current situation. We describe how we have integrated a BDI platform with a commonly used ABMS platform (Repast) to take advantage of this more complex, but well structured, modeling of humans available in BDI programming systems/languages. We also describe a prototype tool to support domain experts and model developers in both understanding and developing the decision making model of an agent using a BDI platform. We also give a brief overview of the RMIT Intelligent Agents group.