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ISCA
2008
IEEE
137views Hardware» more  ISCA 2008»
16 years 14 days ago
Self-Optimizing Memory Controllers: A Reinforcement Learning Approach
Efficiently utilizing off-chip DRAM bandwidth is a critical issue in designing cost-effective, high-performance chip multiprocessors (CMPs). Conventional memory controllers deli...
Engin Ipek, Onur Mutlu, José F. Martí...
ECML
2004
Springer
15 years 11 months ago
Dynamic Asset Allocation Exploiting Predictors in Reinforcement Learning Framework
Given the pattern-based multi-predictors of the stock price, we study a method of dynamic asset allocation to maximize the trading performance. To optimize the proportion of asset ...
Jangmin O, Jae Won Lee, Jongwoo Lee, Byoung-Tak Zh...
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ICRA
2009
IEEE
111views Robotics» more  ICRA 2009»
16 years 22 days ago
Model-based and model-free reinforcement learning for visual servoing
— To address the difficulty of designing a controller for complex visual-servoing tasks, two learning-based uncalibrated approaches are introduced. The first method starts by b...
Amir Massoud Farahmand, Azad Shademan, Martin J&au...
ATAL
2005
Springer
15 years 11 months ago
Improving reinforcement learning function approximators via neuroevolution
Reinforcement learning problems are commonly tackled with temporal difference methods, which use dynamic programming and statistical sampling to estimate the long-term value of ta...
Shimon Whiteson
ATAL
2005
Springer
15 years 11 months ago
Automatic computer game balancing: a reinforcement learning approach
Designing agents whose behavior challenges human players adequately is a key issue in computer games development. This work presents a novel technique, based on reinforcement lear...
Gustavo Andrade, Geber Ramalho, Hugo Santana, Vinc...