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Evolutionary Robotics Lab Notes Karol Zieba - Week of April 7 Neural Network Notes • P1 and P2 are the proprioceptive touch sensors • V1 ...Vn are the vision sensors. Right now they’re probably going to be RGBA. • There will possibly be more than n hidden neurons for the vision sensors, but that’s not been decided yet. An additional m might appear. 0 • Our goal is to have Hi and Hi behave as closely as possible. An alternative would be to instead 0 0 mimic P1 and P2 with H1 and H2 . 1 Experiment Steps Experimental Training 1. Train W1,2 to classify with perception 0 0 2. Train W1 to minimize Ht − Ht • Are the new hidden nodes sufficiently close to make consistent guesses? 0 3. Train W2 to categorize with vision. 0 0 4. Train W1 to predict into future: minimize Ht+1 − Ht 0 • Do we then need to train W2 at the same time? 5. We should approach what visual controller learns. Control Training Train vision from scratch while touch is also enabled. Takeaway The scaling of evolving experiment is better than training vision from scratch. 2 To Do • Find similar work (keyword: cross-modal systems) • Implement Experimental Trainint • Implement Control Training • Implement Vision • Calibrate Touch Sensors • Decide upon the distances to place blocks and their sizes. 3