(Enter summary)
Abstract: Real robots with real sensors are not omniscient. When a robot's
next course of action depends on information that is hidden from
the sensors because of problems such as occlusion, restricted range,
bounded field of view and limited attention, we say the robot suffers
from the hidden state problem. State identification techniques use history
information to uncover hidden state. Some previous approaches
to encoding history include: finite state machines [12, 28], recurrent
neural networks [25]... (Update)
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BibTeX entry: (Update)
McCallum, A. K. (1996a). Hidden state and reinforcement learning with instance-based state identification. http://citeseer.ist.psu.edu/32765.html More
@misc{ mccallum-hidden,
author = "A. McCallum",
title = "Hidden state and reinforcement learning with instance-based state identification",
text = "McCallum, A. K. (1996a). Hidden state and reinforcement learning with instance-based
state identification.",
url = "citeseer.ist.psu.edu/32765.html" }
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