- Diego Perez Liebana, Matthew Stephenson, Raluca D. Gaina, Jochen Renz, Simon M. Lucas:
Introducing real world physics and macro-actions to general video game ai. CIG 2017: 248-255 - Daniele Loiacono, Luca Arnaboldi:
Fight or flight: Evolving maps for cube 2 to foster a fleeing behavior. CIG 2017: 199-206 - Byeong-Jun Min, Kyung-Joong Kim:
Learning to play visual doom using model-free episodic control. CIG 2017: 223-225 - Chanh Nguyen, Noah Reifsnyder, Sriram Gopalakrishnan, Héctor Muñoz-Avila:
Automated learning of hierarchical task networks for controlling minecraft agents. CIG 2017: 226-231 - Hiroya Oonishi, Hitoshi Iima:
Improving generalization ability in a puzzle game using reinforcement learning. CIG 2017: 232-239 - Joseph C. Osborn, Adam Summerville, Michael Mateas:
Automated game design learning. CIG 2017: 240-247 - Luong Huu Phuc, Kanazawa Naoto, Kokolo Ikeda:
Learning human-like behaviors using neuroevolution with statistical penalties. CIG 2017: 207-214 - Andreas Precht Poulsen, Mark Thorhauge, Mikkel Hvilshj Funch, Sebastian Risi:
DLNE: A hybridization of deep learning and neuroevolution for visual control. CIG 2017: 256-263 - Martin L. M. Rooijackers, Mark H. M. Winands:
Resource-gathering algorithms in the game of starcraft. CIG 2017: 264-271 - Andre Santos, Pedro Alexandre Santos, Francisco S. Melo:
Monte Carlo tree search experiments in hearthstone. CIG 2017: 272-279 - Luís Fernando Maia Silva, Windson Viana, Fernando A. M. Trinta:
Using Monte Carlo tree search and google maps to improve game balancing in location-based games. CIG 2017: 215-222 - Sam Snodgrass, Santiago Ontañón:
Procedural level generation using multi-layer level representations with MdMCs. CIG 2017: 280-287 - Matthew Stephenson, Jochen Renz:
Generating varied, stable and solvable levels for angry birds style physics games. CIG 2017: 288-295 - Alberto Uriarte, Santiago Ontañón:
Single believe state generation for partially observable real-time strategy games. CIG 2017: 296-303 - Seonghun Yoon, Kyung-Joong Kim:
Deep Q networks for visual fighting game AI. CIG 2017: 306-308 - Shuyi Zhang, Michael Buro:
Improving hearthstone AI by learning high-level rollout policies and bucketing chance node events. CIG 2017: 309-316 - IEEE Conference on Computational Intelligence and Games, CIG 2017, New York, NY, USA, August 22-25, 2017. IEEE 2017, ISBN 978-1-5386-3233-8 [contents]