Title:
Learning Multi-Modal Control Programs
Learning Multi-Modal Control Programs
Author(s)
Mehta, Tejas R.
Egerstedt, Magnus B.
Egerstedt, Magnus B.
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Abstract
Multi-modal control is a commonly used design tool for breaking up complex control tasks into sequences of simpler tasks. In this paper, we show that by viewing the control space as a set of such tokenized
instructions rather than as real-valued signals, reinforcement learning
becomes applicable to continuous-time control systems. In fact, we show
how a combination of state-space exploration and multi-modal control
converts the original system into a finite state machine, on which Q-learning can be utilized.
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Date Issued
2005-03
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Text
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Book Chapter