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AAAI
2008
13 years 11 months ago
Potential-based Shaping in Model-based Reinforcement Learning
Potential-based shaping was designed as a way of introducing background knowledge into model-free reinforcement-learning algorithms. By identifying states that are likely to have ...
John Asmuth, Michael L. Littman, Robert Zinkov
AAMAS
2005
Springer
13 years 9 months ago
Cooperative Multi-Agent Learning: The State of the Art
Cooperative multi-agent systems are ones in which several agents attempt, through their interaction, to jointly solve tasks or to maximize utility. Due to the interactions among t...
Liviu Panait, Sean Luke
WMTE
2006
IEEE
14 years 3 months ago
Entre-pass: Personalising u-learning with Intelligent Agents
Delivering learning materials anytime, anywhere is the goal underpinning the ubiquitous learning (u-learning) paradigm. Personalising u-learning courseware delivers a unique learn...
Brid C. Doherty, P. T. O'Hare, Michael J. O'Grady,...
CEEMAS
2005
Springer
14 years 2 months ago
A Direct Reputation Model for VO Formation
We show that reputation is a basic ingredient in the Virtual Organisation (VO) formation process. Agents can use their experiences gained in direct past interactions to model other...
Arturo Avila-Rosas, Michael Luck
ATAL
2008
Springer
13 years 11 months ago
Zero-intelligence agents in prediction markets
We construct a novel agent-based model of prediction markets in which putative human qualities like learning, reasoning, and profit-seeking are absent. We show that the prices whi...
Abraham Othman