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AIIDE
2006
15 years 7 months ago
The Self Organization of Context for Learning in MultiAgent Games
Reinforcement learning is an effective machine learning paradigm in domains represented by compact and discrete state-action spaces. In high-dimensional and continuous domains, ti...
Christopher D. White, Dave Brogan
NN
2006
Springer
140views Neural Networks» more  NN 2006»
15 years 6 months ago
Neural mechanism for stochastic behaviour during a competitive game
Previous studies have shown that non-human primates can generate highly stochastic choice behaviour, especially when this is required during a competitive interaction with another...
Alireza Soltani, Daeyeol Lee, Xiao-Jing Wang
CONSTRAINTS
1998
62views more  CONSTRAINTS 1998»
15 years 5 months ago
Learning Game-Specific Spatially-Oriented Heuristics
This paper describes an architecture that begins with enough general knowledge to play any board game as a novice, and then shifts its decision-making emphasis to learned, game-sp...
Susan L. Epstein, Jack Gelfand, Esther Lock
ICRA
2010
IEEE
109views Robotics» more  ICRA 2010»
15 years 4 months ago
A robot companion for inclusive games: A user-centred design perspective
— This article presents the design of Iromec, a modular robot companion tailored towards engaging in social exchanges with children with different disabilities with the aim to em...
Patrizia Marti, Leonardo Giusti
ATAL
2007
Springer
16 years 11 days ago
Using Information Gain to Analyze and Fine Tune the Performance of Supply Chain Trading Agents
The Supply Chain Trading Agent Competition (TAC SCM) was designed to explore approaches to dynamic supply chain trading. During the course of each year’s competition historical d...
James Andrews, Michael Benisch, Alberto Sardinha, ...