Creating Teams of Simple Agents for Specified Tasks: A Computational Complexity Perspective
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Teams of interacting and co-operating agents have been proposed as an efficient and robust alternative to monolithic centralized control for carrying out specified tasks in a variety of applications. A number of different team and agent architectures have been investigated, e.g., teams based on single vs multiple behaviorally-distinct types of agents (homogeneous vs heterogeneous teams), simple vs complex agents, direct vs indirect agent-to-agent communication. A consensus is emerging that (1) heterogeneous teams composed of simple agents that communicate indirectly are preferable and (2) automated methods for verifying and designing such teams are necessary. In this paper, we use computational complexity analysis to assess viable algorithmic options for such automated methods for various types of teams. Building on recent complexity analyses addressing related questions in swarm robotics, we prove that automated team verification and design are by large both exact and approximate polynomial-time intractable in general for the most basic types of homogeneous and heterogeneous teams consisting of simple agents that communicate indirectly. Our results suggest that tractability for these problems must be sought relative to additional restrictions on teams, agents, operating environments, and tasks.
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