Proposal for Multi-Agent Planning that Enables User Interaction and Reactive Action Selection

Abstract

In recent years, there has been a great deal of research on autonomous agents that can achieve their own goals by interacting with the environment through sensors and actuators. Among them, there is research on the architecture of autonomous agents, in which the agent’s overall action selection is determined by multi-agent negotiation, and the agent operates in a real environment. In this paper, we propose an architecture that can cope with dynamic environments, interact with users and other systems, apply optimization algorithms, and achieve multiple goals. It is based on a multi-agent method called ANA, with two extensions: a change in the way sensors, actuators, and planners are arranged, and a change in the way modules in the planner are connected. In order to confirm its effectiveness of it, we performed simulations on a game engine. The results were compared with those of the existing ANA, and it was confirmed that the proposed method enables user interaction and reactive action selection.