robot control using q-learning

Clicks: 342
ID: 180211
2012
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Abstract
This paper focuses on machine learning, where an agent learns how to solve a specific problem. The learning process will take place in a simulated environment, so the effectiveness can be measured without any potential damage to real the robot. QLearning is a temporal-difference learning method, that maps the effectiveness of an action in a given situation. Our learning agents use this method to solve a simple “catch and escape” scenario in a 2D world.
Reference Key
zoltn2012scientificrobot Use this key to autocite in the manuscript while using SciMatic Manuscript Manager or Thesis Manager
Authors ;Szántó Zoltán
Journal biocontrol
Year 2012
DOI
DOI not found
URL
http://scientificbulletin.upm.ro/papers/2012/26_1/ROBOT%20CONTROL%20USING%20Q-LEARNING.pdf
Keywords
Simulation reinforcement learning q-learning civil engineering (general) ε-greedy algorithmengineering (general)

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