Priority-based contextual local decision making in multi-agent systems
Jean-Paul Barthès, Lucile Callebert, Domitile Lourdeaux · 2016
This paper describes a new heuristic approach letting an agent in a multi-agent system make a decision for selecting tasks to undertake. The proposed approach consists in giving the agent a profile including preferences and physical parameters, and a description of its beliefs about the environment. The decision engine allowing the agent to do a specific task is local to the agent and takes into account the agent goals, physical and emotional state and beliefs by combining heuristics priorities for each possible task. The approach is flexible, allowing to model situations where agents represent humans. It can be extended to multiple agents in collaborative environments.