425 search results - page 26 / 85 » Metacognitive Control and Optimal Learning |
108
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GECCO
2008
Springer
14 years 10 months ago
2008
Springer
For artificial entities to achieve high degrees of autonomy they will need to display appropriate adaptability. In this sense adaptability includes representational flexibility gu...
108
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GECCO
2004
Springer
15 years 3 months ago
2004
Springer
In recent years, the evolution of artificial neural networks or neuroevolution has brought promising results in solving difficult reinforcement learning problems. But, like standa...
ICML
2006
IEEE
15 years 10 months ago
2006
IEEE
We present a new, statistical approach to rule learning. Doing so, we address two of the problems inherent in traditional rule learning: The computational hardness of finding rule...
ICANNGA
2007
Springer
15 years 3 months ago
2007
Springer
Reinforcement Learning (RL) is analyzed here as a tool for control system optimization. State and action spaces are assumed to be continuous. Time is assumed to be discrete, yet th...
CDC
2008
IEEE
15 years 4 months ago
2008
IEEE
— The goal of this paper is to develop modeling techniques for complex systems for the purposes of control, estimation, and inference: (i) A new class of Hidden Markov Models is ...