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NN
2007
Springer
105views Neural Networks» more  NN 2007»
13 years 7 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
IPOM
2007
Springer
14 years 1 months ago
Cognitive Network Management with Reinforcement Learning for Wireless Mesh Networks
We present a framework of cognitive network management by means of an autonomic reconfiguration scheme. We propose a network architecture that enables intelligent services to meet ...
Minsoo Lee, Dan Marconett, Xiaohui Ye, S. J. Ben Y...
IWANN
2009
Springer
14 years 2 months ago
Multiagent-Based Educational Environment for Dependents
This paper presents a multiagent architecture that facilitates active learning in educational environments for dependents. The multiagent architecture incorporates agents that can ...
Antonia Macarro, Alberto Pedrero, Juan A. Fraile
IUI
1999
ACM
14 years 20 hour ago
Multi-Agent Learning Approach to WWW Information Retrieval Using Neural Network
er has outlined the potential of multiagent framework for decision support. From an abstract point of view, the concept of an agent has been used as modularization principle for th...
Yong S. Choi, Suk I. Yoo
AIIDE
2008
13 years 10 months ago
Agent Learning using Action-Dependent Learning Rates in Computer Role-Playing Games
We introduce the ALeRT (Action-dependent Learning Rates with Trends) algorithm that makes two modifications to the learning rate and one change to the exploration rate of traditio...
Maria Cutumisu, Duane Szafron, Michael H. Bowling,...