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» Learning Opening Strategy in the Game of Go
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PPSN
2010
Springer
13 years 3 months ago
Indirect Encoding of Neural Networks for Scalable Go
Abstract. The game of Go has attracted much attention from the artificial intelligence community. A key feature of Go is that humans begin to learn on a small board, and then incr...
Jason Gauci, Kenneth O. Stanley
ATAL
2007
Springer
13 years 11 months ago
Reinforcement learning in extensive form games with incomplete information: the bargaining case study
We consider the problem of finding optimal strategies in infinite extensive form games with incomplete information that are repeatedly played. This problem is still open in lite...
Alessandro Lazaric, Jose Enrique Munoz de Cote, Ni...
AI
2010
Springer
13 years 3 months ago
Agent decision-making in open mixed networks
Computer systems increasingly carry out tasks in mixed networks, that is in group settings in which they interact both with other computer systems and with people. Participants in...
Ya'akov Gal, Barbara J. Grosz, Sarit Kraus, Avi Pf...
TCIAIG
2010
12 years 11 months ago
Learning to Drive in the Open Racing Car Simulator Using Online Neuroevolution
In this paper, we applied online neuroevolution to evolve nonplayer characters for The Open Racing Car Simulator (TORCS). While previous approaches allowed online learning with per...
Luigi Cardamone, Daniele Loiacono, Pier Luca Lanzi
ATAL
2011
Springer
12 years 4 months ago
Using iterated reasoning to predict opponent strategies
The field of multiagent decision making is extending its tools from classical game theory by embracing reinforcement learning, statistical analysis, and opponent modeling. For ex...
Michael Wunder, Michael Kaisers, John Robert Yaros...