BibTeX
@MISC{Jervis93connectionistadaptive,
author = {Timothy Tristram Jervis},
title = {Connectionist Adaptive Control},
year = {1993}
}
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Abstract
The work considers a general framework for learning control, known as reinforcement learning. It documents the first application of a reinforcement learning controller to the task of regulating an inverted pendulum in hardware. It explores the application of non-linear parametric models known as connectionist models, or neural networks, to learning control. It approaches learning control as an optimization problem, and proposes a promising new learning control algorithm. The algorithm comprises two optimisations - the first learns what the task is, the second learns how to complete the task efficiently.
