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» A Learning Architecture for the Game of Go
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AAI
2010
195views more  AAI 2010»
13 years 3 months ago
Automatic Extraction of Go Game Positions from Images: a Multi-Strategical Approach to Constrained Multi-Object Recognition
Here, we present a constrained object recognition task that has been robustly solved largely with simple machine learning methods, using a small corpus of about 100 images taken u...
Alexander K. Seewald
ICMLA
2003
13 years 7 months ago
A Distributed Reinforcement Learning Approach to Pattern Inference in Go
— This paper shows that the distributed representation found in Learning Vector Quantization (LVQ) enables reinforcement learning methods to cope with a large decision search spa...
Myriam Abramson, Harry Wechsler
AGENTS
2001
Springer
13 years 10 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
ICGA
2007
157views Optimization» more  ICGA 2007»
13 years 6 months ago
Computing "Elo Ratings" of Move Patterns in the Game of Go
Abstract. Move patterns are an essential method to incorporate domain knowledge into Go-playing programs. This paper presents a new Bayesian technique for supervised learning of su...
Rémi Coulom
ICANN
2010
Springer
13 years 6 months ago
Multi-Dimensional Deep Memory Atari-Go Players for Parameter Exploring Policy Gradients
Abstract. Developing superior artificial board-game players is a widelystudied area of Artificial Intelligence. Among the most challenging games is the Asian game of Go, which, des...
Mandy Grüttner, Frank Sehnke, Tom Schaul, J&u...