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» Metacognitive Control and Optimal Learning
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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
DATE
2008
IEEE
136views Hardware» more  DATE 2008»
16 years 11 days 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
ICRA
2009
IEEE
130views Robotics» more  ICRA 2009»
16 years 17 days 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»
16 years 2 days 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
GECCO
2005
Springer
132views Optimization» more  GECCO 2005»
15 years 11 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