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» Constructing States for Reinforcement Learning
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IJSNET
2006
145views more  IJSNET 2006»
15 years 4 months ago
RL-MAC: a reinforcement learning based MAC protocol for wireless sensor networks
:This paper introduces RL-MAC, a novel adaptive MediaAccess Control (MAC) protocol for Wireless Sensor Networks (WSN) that employs a reinforcement learning framework. Existing sche...
Zhenzhen Liu, Itamar Elhanany
ICML
1999
IEEE
16 years 5 months ago
Implicit Imitation in Multiagent Reinforcement Learning
Imitation is actively being studied as an effective means of learning in multi-agent environments. It allows an agent to learn how to act well (perhaps optimally) by passively obs...
Bob Price, Craig Boutilier
EWRL
2008
15 years 6 months ago
Efficient Reinforcement Learning in Parameterized Models: Discrete Parameter Case
We consider reinforcement learning in the parameterized setup, where the model is known to belong to a parameterized family of Markov Decision Processes (MDPs). We further impose ...
Kirill Dyagilev, Shie Mannor, Nahum Shimkin
ECAI
2010
Springer
15 years 5 months ago
The Dynamics of Multi-Agent Reinforcement Learning
Abstract. Infinite-horizon multi-agent control processes with nondeterminism and partial state knowledge have particularly interesting properties with respect to adaptive control, ...
Luke Dickens, Krysia Broda, Alessandra Russo
ML
2002
ACM
121views Machine Learning» more  ML 2002»
15 years 3 months ago
Near-Optimal Reinforcement Learning in Polynomial Time
We present new algorithms for reinforcement learning, and prove that they have polynomial bounds on the resources required to achieve near-optimal return in general Markov decisio...
Michael J. Kearns, Satinder P. Singh