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DOI: http://dx.doi.org/10.7551/978-0-262-33936-0-ch024
Page 108
First published July 1 2016

Evolving Real-time Heuristic Search Algorithms

Vadim Bulitko

Abstract (Excerpt)

Heuristic search is a core area of Artificial Intelligence, successfully applied to planning, constraint satisfaction and game playing. In real-time heuristic search autonomous agents interleave planning and plan execution and access environment locally which make them more suitable for Artificial Life style settings. Over the last two decades a large number of real-time heuristic search algorithms have been manually crafted and evaluated. In this paper we break down several published algorithms into building blocks and then let a simulated evolution re-combine the blocks in a performance-based way. Remarkably, even relatively short evolution runs result in algorithms with state-of-the-art performance. These promising preliminary results open exciting possibilities in the field of real-time heuristic search.