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» Metacognitive Control and Optimal Learning
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ATAL
2005
Springer
15 years 3 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
DATE
2008
IEEE
136views Hardware» more  DATE 2008»
15 years 4 months ago
A Framework of Stochastic Power Management Using Hidden Markov Model
- The effectiveness of stochastic power management relies on the accurate system and workload model and effective policy optimization. Workload modeling is a machine learning proce...
Ying Tan, Qinru Qiu
66
Voted
ICRA
2009
IEEE
130views Robotics» more  ICRA 2009»
15 years 4 months ago
Model adaptation with least-squares SVM for adaptive hand prosthetics
— The state-of-the-art in control of hand prosthetics is far from optimal. The main control interface is represented by surface electromyography (EMG): the activation potentials ...
Francesco Orabona, Claudio Castellini, Barbara Cap...
GECCO
2007
Springer
172views Optimization» more  GECCO 2007»
15 years 3 months ago
A simulation of evolved autotrophic reproduction
In this experiment we evolve reproductive behaviors for a simulated vehicle. Future work will employ the resulting behaviors to populate a simulated ecosystem. Categories and Subj...
Correy Allen Kowall, Brian J. Krent
70
Voted
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 3 months ago
Evolving computer intrusion scripts for vulnerability assessment and log analysis
Evolutionary computation is used to construct undetectable computer attack scripts. Using a simulated operating system, we show that scripts can be evolved to cover their tracks a...
Julien Budynek, Eric Bonabeau, Ben Shargel