Introduction to algorithms
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy set theory—and its applications (3rd ed.)
Fuzzy sets as a basis for a theory of possibility
Fuzzy Sets and Systems
AI Game Programming Wisdom
AI Game Programming Wisdom
Moving-Target Search: A Real-Time Search for Changing Goals
IEEE Transactions on Pattern Analysis and Machine Intelligence
Controlling the learning process of real-time heuristic search
Artificial Intelligence
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
Learning in real-time search: a unifying framework
Journal of Artificial Intelligence Research
Cops and robber game without recharging
SWAT'10 Proceedings of the 12th Scandinavian conference on Algorithm Theory
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In a computer game, equipping a bot with a suitable algorithm to locate a human player is difficult. Besides the unpredictable moves made by the player, an unexplored map region poses additional constraints such as new obstacles and pathways that the bot needs to discover quickly. The design criteria of such moving target search (MTS) algorithms would typically need to consider computation efficiency and storage requirements. That is, the bot must appear to be “smart” and “quick” in order to enhance the playability and challenge posed by the game. These criteria, however, pose conflicting requirements. In this article, we study and evaluate the performance and behavior of two novel MTS algorithms, Fuzzy MTS and Abstraction MTS, against existing MTS algorithms in randomly generated mazes of increasing size. Simulations reveal that Fuzzy MTS and Abstraction MTS exhibit competitive performance even with large problem spaces.