Decentralized opportunistic navigation strategies for multi-agent systems in the presence of an adversary

We investigate a jamming attack on the communication network of a multi-agent system in a formation. We propose a communication and motion model for the agents. The communication model provides a relation in the spatial domain for effective jamming by an intruder.We formulate the problem as a zero-sum pursuit-evasion game. In our earlier work we used Isaacs' approach to obtain motion strategies for a network of agents to evade the jamming attack. In this work, we imagine a scenario in which each agent has a knowledge about the value function under perfect state information, beforehand. Due to lack of information about all the agents in the team each agent is constrained to make a local decision based on the information about his neighbors. We propose on-line algorithms under decentralized information patterns which converge for each player. We propose approximation algorithms for the agents, based on averaging and provide some bounds on their performance.