Communication-Free Distributed Coverage for Networked Systems
This addresses the challenge of efficient network coverage for systems with limited communication capabilities, though it appears incremental as it builds on existing game-theoretic methods.
The paper tackles the problem of distributed coverage of a network by mobile agents without communication, using a game-theoretic approach to optimize agent locations based on local sensing, achieving coverage through a decentralized algorithm.
In this paper, we present a communication-free algorithm for distributed coverage of an arbitrary network by a group of mobile agents with local sensing capabilities. The network is represented as a graph, and the agents are arbitrarily deployed on some nodes of the graph. Any node of the graph is covered if it is within the sensing range of at least one agent. The agents are mobile devices that aim to explore the graph and to optimize their locations in a decentralized fashion by relying only on their sensory inputs. We formulate this problem in a game theoretic setting and propose a communication-free learning algorithm for maximizing the coverage.