The Observation-based Model for BDI-Agents

We present a new computational model of BDI-agents, called the observation-based BDI-model. The key point of this BDImodel is to express agents’ beliefs, desires and intentions as a set of runs (computing paths), which is exactly a system in the interpreted system model, a well-known agent model due to Halpern and his colleagues. Our BDI-model is computationally grounded in that we are able to associate the BDIagent model with a computer program, and formulas, involving agents’ beliefs, desires (goals) and intentions, can be understood as properties of program computations. We present a sound and complete proof system with respect to our BDImodel and explore how symbolic model checking techniques can be applied to model checking BDI-agents. In order to make our BDI-model more flexible and practically realistic, we generalize it so that agents can have multiple sources of beliefs, multiple goals and intentions.