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NIPS
1997
13 years 9 months ago
Reinforcement Learning with Hierarchies of Machines
We present a new approach to reinforcement learning in which the policies considered by the learning process are constrained by hierarchies of partially specified machines. This ...
Ronald Parr, Stuart J. Russell
BC
1998
109views more  BC 1998»
13 years 7 months ago
Learning and stabilization of altruistic behaviors in multi-agent systems by reciprocity
Optimization of performance in collective systems often requires altruism. The emergence and stabilization of altruistic behaviors are dicult to achieve because the agents incur ...
Javier Zamora, José del R. Millán, A...
ICIDS
2009
Springer
14 years 2 months ago
Directorial Control in a Decision-Theoretic Framework for Interactive Narrative
Computer aided interactive narrative has received increasing attention in recent years. Automated directorial control that manages the development of the story in the face of user ...
Mei Si, Stacy C. Marsella, David V. Pynadath
ATAL
2006
Springer
13 years 11 months ago
Learning the required number of agents for complex tasks
Coordinating agents in a complex environment is a hard problem, but it can become even harder when certain characteristics of the tasks, like the required number of agents, are un...
Sébastien Paquet, Brahim Chaib-draa
AAAI
2010
13 years 9 months ago
Multi-Agent Learning with Policy Prediction
Due to the non-stationary environment, learning in multi-agent systems is a challenging problem. This paper first introduces a new gradient-based learning algorithm, augmenting th...
Chongjie Zhang, Victor R. Lesser