Programming deliberation strategies in meta-APL - Leask, Sam; Logan, Brian (2015)
A key advantage of BDI-based agent programming is that agents can deliberate about which course of action to adopt to achieve a goal or respond to an event. However, while state-of-the-art BDI-based agent programming languages provide flexible support for expressing plans, they are typically limited to a single, hard-coded, deliberation strategy (perhaps with some parameterisation) for all task environments. In this paper, we present an alternative approach. We show how both agent programs and the agent’s deliberation strategy can be encoded in the agent programming language meta-APL. Key steps in the execution cycle of meta-APL are reflected in the state of the agent and can be queried and updated by meta-APL rules, allowing BDI deliberation strategies to be programmed with ease. To illustrate the flexibility of meta-APL, we show how three typical BDI deliberation strategies can be programmed using meta-APL rules. We then show how meta-APL can used to program a novel adaptive deliberation strategy that avoids interference between intentions.