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We study two player pursuit-evasion games with concurrent moves, infinite horizon, and discounted rewards. The players have partial observability, however, the evader is given an advantage of knowing the current position of the units of the pursuer. We show that (1) value functions of this game depend only on the position of the pursuing units and the belief the pursuer has about the position o...

Tag is a children’s game based on symmetrical pursuit and evasion. In the experiments described here, control programs for mobile agents (simulated vehicles) are evolved based on their skill at the game of tag. A player’s fitness is determined by how well it performs when placed in competition with several opponents chosen randomly from the coevolving population of players. In the beginning, th...

We study a two-player pursuit-evasion game, in which an agent moving amongst obstacles is to be maintained within “sight” of a pursuing robot. Using a discretization of the environment, our main contribution is to design an efficient algorithm that decides, given initial positions of both pursuer and evader, if the evader can take any moving strategy to go out of sight of the pursuer at any tim...

Robots playing games that humans are adept in is a challenge. We studied robotic agents playing Chain Catch game as a Multi-Agent System (MAS). Our game starts with a traditional Catch game similar to Pursuit evasion, and further extends it to form a growing chain of predator agents to chase remaining preys. Hence Chain Catch is a combination of two challenges pursuit domain and robotic chain f...

Current successes in artificial intelligence domain have revitalized interest spacecraft pursuit-evasion game, which is an interception problem with a non-cooperative maneuvering target. The paper presents automated machine learning (AutoML) based method to generate optimal trajectories long-distance scenarios. Compared conventional deep neural network (DNN) methods, the proposed dramatically r...