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» Model Checking Markov Reward Models with Impulse Rewards
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ATAL
2008
Springer
14 years 11 days ago
Expediting RL by using graphical structures
The goal of Reinforcement learning (RL) is to maximize reward (minimize cost) in a Markov decision process (MDP) without knowing the underlying model a priori. RL algorithms tend ...
Peng Dai, Alexander L. Strehl, Judy Goldsmith
ICC
2009
IEEE
151views Communications» more  ICC 2009»
13 years 8 months ago
Performance Evaluation of Multiple-Relay Cooperative ARQ Strategies for Mobile Networks
In Cooperative Automatic Repeat reQuest (C-ARQ) protocols, one or more nodes can act as relays, collaborating in the frame retransmission process between a sender and a destination...
Juan J. Alcaraz, Joan García-Haro
NIPS
2008
13 years 11 months ago
Goal-directed decision making in prefrontal cortex: a computational framework
Research in animal learning and behavioral neuroscience has distinguished between two forms of action control: a habit-based form, which relies on stored action values, and a goal...
Matthew Botvinick, James An
AAAI
2011
12 years 10 months ago
Learned Behaviors of Multiple Autonomous Agents in Smart Grid Markets
One proposed approach to managing a large complex Smart Grid is through Broker Agents who buy electrical power from distributed producers, and also sell power to consumers, via a ...
Prashant P. Reddy, Manuela M. Veloso
IROS
2009
IEEE
154views Robotics» more  IROS 2009»
14 years 5 months ago
Consideration on robotic giant-swing motion generated by reinforcement learning
—This study attempts to make a compact humanoid robot acquire a giant-swing motion without any robotic models by using reinforcement learning; only the interaction with environme...
Masayuki Hara, Naoto Kawabe, Naoki Sakai, Jian Hua...