Artificial Intelligence
Artificial intelligence: a modern approach
Artificial intelligence: a modern approach
Artificial intelligence and soft computing: behavioral and cognitive modeling of the human brain
Artificial intelligence and soft computing: behavioral and cognitive modeling of the human brain
Computer Networks
Moving-Target Search: A Real-Time Search for Changing Goals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Evolving Beharioral Strategies in Predators and Prey
IJCAI '95 Proceedings of the Workshop on Adaption and Learning in Multi-Agent Systems
Speeding up the Convergence of Real-Time Search
Proceedings of the Seventeenth National Conference on Artificial Intelligence and Twelfth Conference on Innovative Applications of Artificial Intelligence
Eighteenth national conference on Artificial intelligence
Controlling the learning process of real-time heuristic search
Artificial Intelligence
COOPERATIVE COEVOLUTION OF MULTI-AGENT SYSTEMS
COOPERATIVE COEVOLUTION OF MULTI-AGENT SYSTEMS
A framework and analysis for cooperative search using UAV swarms
Proceedings of the 2004 ACM symposium on Applied computing
Incremental heuristic search in AI
AI Magazine
A Comparison of Fast Search Methods for Real-Time Situated Agents
AAMAS '04 Proceedings of the Third International Joint Conference on Autonomous Agents and Multiagent Systems - Volume 2
Bounds on the Travel Cost of a Mars Rover Prototype Search Heuristic
SIAM Journal on Discrete Mathematics
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Real time target evaluation search
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
RTTES: Real-time search in dynamic environments
Applied Intelligence
A layered approach to learning coordination knowledge in multiagent environments
Applied Intelligence
Speeding up moving-target search
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems
Are many reactive agents better than a few deliberative ones?
IJCAI'93 Proceedings of the 13th international joint conference on Artifical intelligence - Volume 1
Multiple agents moving target search
IJCAI'03 Proceedings of the 18th international joint conference on Artificial intelligence
Real-time path planning for humanoid robot navigation
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
IJCAI'05 Proceedings of the 19th international joint conference on Artificial intelligence
The focussed D* algorithm for real-time replanning
IJCAI'95 Proceedings of the 14th international joint conference on Artificial intelligence - Volume 2
Real-time moving target evaluation search
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Fast replanning for navigation in unknown terrain
IEEE Transactions on Robotics
Real-Time Edge Follow: A Real-Time Path Search Approach
IEEE Transactions on Systems, Man, and Cybernetics, Part C: Applications and Reviews
Proceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 1
Toward opportunistic collaboration in target pursuit problems
AIS'11 Proceedings of the Second international conference on Autonomous and intelligent systems
Empirical evaluation of ad hoc teamwork in the pursuit domain
The 10th International Conference on Autonomous Agents and Multiagent Systems - Volume 2
An analysis framework for ad hoc teamwork tasks
Proceedings of the 11th International Conference on Autonomous Agents and Multiagent Systems - Volume 1
On Confinement of the Initial Location of an Intruder in a Multi-robot Pursuit Game
Journal of Intelligent and Robotic Systems
Learning collaborative team behavior from observation
Expert Systems with Applications: An International Journal
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In this paper, we address the problem of multi-agent pursuit in dynamic and partially observable environments, modeled as grid worlds; and present an algorithm called Multi-Agent Real-Time Pursuit (MAPS) for multiple predators to capture a moving prey cooperatively. MAPS introduces two new coordination strategies namely Blocking Escape Directions and Using Alternative Proposals, which help the predators waylay the possible escape directions of the prey in coordination. We compared our coordination strategies with the uncoordinated one against a prey controlled by Prey A*, and observed an impressive reduction in the number of moves to catch the prey.