Game theory is the study of decision problems in which there are multiple decision makers
and the quality of a decision maker's choice depends on both that choice and the choices of …

This paper reviews a series of works done on the multi-agent perimeter defense scenario, in
which a team of intruders try to score by reaching the target region while a team of defenders …

Recently, deep reinforcement learning (RL) methods have been applied successfully to
multi-agent scenarios. Typically, the observation vector for decentralized decision making is …

Pursuit-evasion is the problem of capturing mobile targets with one or more pursuers. We
use deep reinforcement learning for pursuing an omnidirectional target with multiple …

In this article an N-pursuer versus M-evader team conflict is studied. This article extends
classical differential game theory to simultaneously address weapon assignments and …

In this paper, we consider a pursuit-evasion game in which multiple pursuers attempt to
capture one superior evader. A distributed cooperative pursuit strategy with communication …

This paper studies a multi-player game between intruders and defenders. The intruder team
tries to score by sending as many intruders as possible to the target. The defender team tries …

This paper is concerned with a scenario of active target defense modeled as a zero-sum
differential game. The differential game theory as developed by Isaacs provides the correct …

It is of great challenge, though promising, to coordinate collective robots for hunting an
evader in a decentralized manner purely in light of local observations. In this paper, this …

We propose a distributed algorithm for the cooperative pursuit of multiple evaders using
multiple pursuers in a bounded convex environment. The algorithm is suitable for …