Commercial games can be an excellent testbed to artificial intelligence (AI) research, being a middle ground between synthetic, highly abstracted academic benchmarks, and more intricate problems from real life. Among the many AI techniques and problems relevant to games, such as learning, planning, and natural language processing, pathfinding stands out as one of the most common applications of AI research to games. In this document we survey recent work in pathfinding in games. Then we identify some challenges and potential directions for future work. This chapter summarizes the discussions held in the pathfinding workgroup.
@InCollection{botea_et_al:DFU.Vol6.12191.21, author = {Botea, Adi and Bouzy, Bruno and Buro, Michael and Bauckhage, Christian and Nau, Dana}, title = {{Pathfinding in Games}}, booktitle = {Artificial and Computational Intelligence in Games}, pages = {21--31}, series = {Dagstuhl Follow-Ups}, ISBN = {978-3-939897-62-0}, ISSN = {1868-8977}, year = {2013}, volume = {6}, editor = {Lucas, Simon M. and Mateas, Michael and Preuss, Mike and Spronck, Pieter and Togelius, Julian}, publisher = {Schloss Dagstuhl -- Leibniz-Zentrum f{\"u}r Informatik}, address = {Dagstuhl, Germany}, URL = {https://drops.dagstuhl.de/entities/document/10.4230/DFU.Vol6.12191.21}, URN = {urn:nbn:de:0030-drops-43334}, doi = {10.4230/DFU.Vol6.12191.21}, annote = {Keywords: path finding, search, games} }
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