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CIMCA
2006
IEEE
15 years 9 months ago
Model-driven Walks for Resource Discovery in Peer-to-Peer Networks
In this paper, a distributed and adaptive approach for resource discovery in peer-to-peer networks is presented. This approach is based on the mobile agent paradigm and the random...
Mohamed Bakhouya, Jaafar Gaber
160
Voted
NN
2007
Springer
105views Neural Networks» more  NN 2007»
15 years 2 months ago
Guiding exploration by pre-existing knowledge without modifying reward
Reinforcement learning is based on exploration of the environment and receiving reward that indicates which actions taken by the agent are good and which ones are bad. In many app...
Kary Främling
ICML
2006
IEEE
16 years 4 months ago
Using inaccurate models in reinforcement learning
In the model-based policy search approach to reinforcement learning (RL), policies are found using a model (or "simulator") of the Markov decision process. However, for ...
Pieter Abbeel, Morgan Quigley, Andrew Y. Ng
ICML
2004
IEEE
16 years 4 months ago
Convergence of synchronous reinforcement learning with linear function approximation
Synchronous reinforcement learning (RL) algorithms with linear function approximation are representable as inhomogeneous matrix iterations of a special form (Schoknecht & Merk...
Artur Merke, Ralf Schoknecht
ICML
2002
IEEE
16 years 4 months ago
Hierarchically Optimal Average Reward Reinforcement Learning
Two notions of optimality have been explored in previous work on hierarchical reinforcement learning (HRL): hierarchical optimality, or the optimal policy in the space defined by ...
Mohammad Ghavamzadeh, Sridhar Mahadevan