Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal With It

Authors

  • Davide Tateo Politecnico di Milano
  • Jacopo Banfi Politecnico di Milano
  • Alessandro Riva Politecnico di Milano
  • Francesco Amigoni Politecnico di Milano
  • Andrea Bonarini Politecnico di Milano

DOI:

https://doi.org/10.1609/aaai.v32i1.11587

Keywords:

Multiagent Path Planning, Connected Path Planning, Planning on graphs

Abstract

In the Multiagent Connected Path Planning problem (MCPP), a team of agents moving in a graph-represented environment must plan a set of start-goal joint paths which ensures global connectivity at each time step, under some communication model. The decision version of this problem asking for the existence of a plan that can be executed in at most a given number of steps is claimed to be NP-complete in the literature. The NP membership proof, however, is not detailed. In this paper, we show that, in fact, even deciding whether a feasible plan exists is a PSPACE-complete problem. Furthermore, we present three algorithms adopting different search paradigms, and we empirically show that they may efficiently obtain a feasible plan, if any exists, in different settings.

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Published

2018-04-26

How to Cite

Tateo, D., Banfi, J., Riva, A., Amigoni, F., & Bonarini, A. (2018). Multiagent Connected Path Planning: PSPACE-Completeness and How to Deal With It. Proceedings of the AAAI Conference on Artificial Intelligence, 32(1). https://doi.org/10.1609/aaai.v32i1.11587

Issue

Section

AAAI Technical Track: Multiagent Systems