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» Predicting Opponent Actions by Observation
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115
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ECAI
2006
Springer
15 years 5 months ago
Strategic Foresighted Learning in Competitive Multi-Agent Games
We describe a generalized Q-learning type algorithm for reinforcement learning in competitive multi-agent games. We make the observation that in a competitive setting with adaptive...
Pieter Jan't Hoen, Sander M. Bohte, Han La Poutr&e...
122
Voted
ML
2006
ACM
113views Machine Learning» more  ML 2006»
15 years 1 months ago
Learning to bid in bridge
Bridge bidding is considered to be one of the most difficult problems for game-playing programs. It involves four agents rather than two, including a cooperative agent. In additio...
Asaf Amit, Shaul Markovitch
AGENTS
2001
Springer
15 years 6 months ago
It knows what you're going to do: adding anticipation to a Quakebot
The complexity of AI characters in computer games is continually improving; however they still fall short of human players. In this paper we describe an AI bot for the game Quake ...
John E. Laird
COLT
2006
Springer
15 years 5 months ago
Online Learning with Variable Stage Duration
We consider online learning in repeated decision problems, within the framework of a repeated game against an arbitrary opponent. For repeated matrix games, well known results esta...
Shie Mannor, Nahum Shimkin
AAAI
2012
13 years 4 months ago
Competing with Humans at Fantasy Football: Team Formation in Large Partially-Observable Domains
We present the first real-world benchmark for sequentiallyoptimal team formation, working within the framework of a class of online football prediction games known as Fantasy Foo...
Tim Matthews, Sarvapali D. Ramchurn, Georgios Chal...