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ATAL
2007
Springer
14 years 1 months ago
Multiagent reinforcement learning and self-organization in a network of agents
To cope with large scale, agents are usually organized in a network such that an agent interacts only with its immediate neighbors in the network. Reinforcement learning technique...
Sherief Abdallah, Victor R. Lesser
LWA
2007
13 years 9 months ago
Towards Learning User-Adaptive State Models in a Conversational Recommender System
Typical conversational recommender systems support interactive strategies that are hard-coded in advance and followed rigidly during a recommendation session. In fact, Reinforceme...
Tariq Mahmood, Francesco Ricci
ML
1998
ACM
101views Machine Learning» more  ML 1998»
13 years 7 months ago
Elevator Group Control Using Multiple Reinforcement Learning Agents
Recent algorithmic and theoretical advances in reinforcement learning (RL) have attracted widespread interest. RL algorithmshave appeared that approximatedynamic programming on an ...
Robert H. Crites, Andrew G. Barto
NIPS
2003
13 years 9 months ago
Learning a World Model and Planning with a Self-Organizing, Dynamic Neural System
We present a connectionist architecture that can learn a model of the relations between perceptions and actions and use this model for behavior planning. State representations are...
Marc Toussaint
CCECE
2006
IEEE
14 years 1 months ago
A Dynamic Associative E-Learning Model based on a Spreading Activation Network
Presenting information to an e-learning environment is a challenge, mostly, because ofthe hypertextlhypermedia nature and the richness ofthe context and information provides. This...
Phongchai Nilas, Nilamit Nilas, Somsak Mitatha