🤖 AI Summary
Existing BDI agent planning approaches rely heavily on manual design and are predominantly limited to single-agent settings, rendering them inadequate for modeling collaborative or competitive dynamics in multi-agent systems. Method: This paper introduces Alternating-Time Temporal Logic (ATL) into the BDI framework for the first time, proposing an automated plan generation method for multi-agent systems. Group-level objectives—such as “cooperatively achieve” or “competitively prevent”—are formally specified in ATL, and model checking is employed to synthesize BDI plans satisfying inter-agent interaction constraints. Contribution/Results: The approach significantly reduces human intervention and supports dynamic, asymmetric multi-agent interactions. Empirical evaluation on cooperative game tasks demonstrates that the generated plans effectively coordinate agents toward shared goals, validating the method’s feasibility and practical utility.
📝 Abstract
Belief-Desire-Intention (BDI) is a framework for modelling agents based on their beliefs, desires, and intentions. Plans are a central component of BDI agents, and define sequences of actions that an agent must undertake to achieve a certain goal. Existing approaches to plan generation often require significant manual effort, and are mainly focused on single-agent systems. As a result, in this work, we have developed a tool that automatically generates BDI plans using Alternating-Time Temporal Logic (ATL). By using ATL, the plans generated accommodate for possible competition or cooperation between the agents in the system. We demonstrate the effectiveness of the tool by generating plans for an illustrative game that requires agent collaboration to achieve a shared goal. We show that the generated plans allow the agents to successfully attain this goal.