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Encoding Robotic Sensor States for Q-Learning using the

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Encoding Robotic Sensor States for Q-Learning using the Self-Organizing Map Gabriel J. Ferrer Department of Computer Science Hendrix College
Outline ,[object Object],[object Object],[object Object],[object Object],[object Object]
Statement of Problem ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Robotic Platform
Experimental Task ,[object Object],[object Object]
Q-Learning ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],Q-Learning and Robots
Creating Discrete Inputs ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Self-Organizing Map (SOM)‏ ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Applying the SOM ,[object Object],[object Object],[object Object],[object Object],[object Object]
SOM Unsupervised Learning ,[object Object],[object Object],[object Object],[object Object],[object Object]
Experiments ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Rewards ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Parameters ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Experimental Controls ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
SOM Formulations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
SOM Formulations ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Quantitative Results 0.07 0.11 0.2 0.05 0.1 0.1 StDv/It 0.68 0.57 0.67 0.59 0.72 0.76 Mean/It 594.5 547.22 661.59 495 540.55 723 Max 481.55 378.72 354.25 410.2 528.67 506.47 Min 560.77 442.62 587.64 485.11 667.5 608.75 Median 57.98 85.07 160.41 39.39 76.95 81.92 StDv 545.61 456.19 534.49 468.86 578.91 607.97 Mean QTb QTa QSOMb QSOMa Qb Qa
Qualitative Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Qualitative Results ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Experimental Area
First Movie ,[object Object],[object Object],[object Object]
Second Movie ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]
Discussion ,[object Object],[object Object],[object Object],[object Object],[object Object],[object Object],[object Object]

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Encoding Robotic Sensor States for Q-Learning using the

  • 1. Encoding Robotic Sensor States for Q-Learning using the Self-Organizing Map Gabriel J. Ferrer Department of Computer Science Hendrix College
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  • 18. Quantitative Results 0.07 0.11 0.2 0.05 0.1 0.1 StDv/It 0.68 0.57 0.67 0.59 0.72 0.76 Mean/It 594.5 547.22 661.59 495 540.55 723 Max 481.55 378.72 354.25 410.2 528.67 506.47 Min 560.77 442.62 587.64 485.11 667.5 608.75 Median 57.98 85.07 160.41 39.39 76.95 81.92 StDv 545.61 456.19 534.49 468.86 578.91 607.97 Mean QTb QTa QSOMb QSOMa Qb Qa
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