128 search results - page 18 / 26 » Hierarchically Optimal Average Reward Reinforcement Learning |
CORR
2012
Springer
12 years 3 months ago
2012
Springer
Reinforcement learning addresses the dilemma between exploration to find profitable actions and exploitation to act according to the best observations already made. Bandit proble...
CEC
2005
IEEE
13 years 9 months ago
2005
IEEE
We apply XCS with computed prediction (XCSF) to tackle multistep reinforcement learning problems involving continuous inputs. In essence we use XCSF as a method of generalized rein...
ISCA
2008
IEEE
14 years 2 months ago
2008
IEEE
Efficiently utilizing off-chip DRAM bandwidth is a critical issue in designing cost-effective, high-performance chip multiprocessors (CMPs). Conventional memory controllers deli...
IEEEPACT
2008
IEEE
14 years 2 months ago
2008
IEEE
Communication overheads are one of the fundamental challenges in a multiprocessor system. As the number of processors on a chip increases, communication overheads and the distribu...
AAAI
2008
13 years 10 months ago
2008
Hierarchical state decompositions address the curse-ofdimensionality in Q-learning methods for reinforcement learning (RL) but can suffer from suboptimality. In addressing this, w...