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. 2014 Jan 6;7:25. doi: 10.3389/fnbot.2013.00025

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Copyright © 2014 Frank, Leitner, Stollenga, Förster and Schmidhuber.

This is an open-access article distributed under the terms of the Creative Commons Attribution License (CC BY). The use, distribution or reproduction in other forums is permitted, provided the original author(s) or licensor are credited and that the original publication in this journal is cited, in accordance with accepted academic practice. No use, distribution or reproduction is permitted which does not comply with these terms.

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The learned single-arm MDP planner. The 4D state space is labeled as follows: shoulder flexion/extension (1,2,3), arm abduction/adduction (a,b,c), lateral/medial arm rotation (I,II,III), elbow flexion/extension (A,B,C). Each color represents an interesting state-action, which often takes the agent to some unexpected state. Each arrow of a particular color represents a state transition probability and the weight of the arrow is proportional to the magnitude of that probability. Arrows in gray represent boring state-actions. These work as expected, reliably taking the agent to the intended goal state, to which they point.