- Successfully implemented Q-Learning for a simple robot navigation problem of a robot moving on a 5 x 5 grid with one arbitrary goal (reward of +10) and three arbitrary obstacles (reward of -10)
- Algorithm used is:
- Initialize q-table with all zeroes
- Loop
- Pick a random start state, action(s,a) transition
- make transistion from(s,a) -> s’
- receive reward
- Update Q(s,a) <- R(s,a) + gamma*(max(Q(s’,for all actions possible from next state)))
- Run from main.m
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