Q-Learning

More documents

Recommendations

Info

Update Q(s2, a23) s1, a12 0 s1, a14 0 s2, a21 0 s2, a23 0 s2, a25 0 s3, a32 0 s3, a36 0 s4, a41 0 s4, a45 0 s5, a54 0 s5, a52 0 Current Position: Red Available actions: a32, a36 Update Q(s1, a12): Q(s2, a23) = r + .5 * max(Q(s3,a32), Q(s3,a36)) = 0 a12 s1 s2 s3 a14 a41 a21 a45 a25 a52 a23 a32 a56 s4 s5 End: s6 a54 a36
Next Move s1, a12 0 s1, a14 0 s2, a21 0 s2, a23 0 s2, a25 0 s3, a32 0 s3, a36 0 s4, a41 0 s4, a45 0 s5, a54 0 s5, a52 0 Current Position: Red Available actions: a32, a36 Chose a36 a12 s1 s2 s3 a14 a41 a21 a45 s4 s5 End: s6 a54 a25 a52 a23 a32 a56 a36
Page 1 and 2: Q-Learning ● ● ● Reinforcemen
Page 3 and 4: Our Problem ● ● ● ● ● We
Page 5 and 6: Formal Definition Q s , a=r s ,amax
Page 7 and 8: Example Problem a12 a23 s1 s2 s3 a2
Page 9 and 10: The Algorithm s1, a12 0 s1, a14 0 s
Page 11: Next Move s1, a12 0 s1, a14 0 s2, a
Page 15 and 16: New Game s1, a12 0 s1, a14 0 s2, a2
Page 17 and 18: Final State (after many iterations)
Page 19 and 20: Neural Network Approximation ●
Page 21 and 22: Exploration Strategy ● ● ● Wa

Q-Learning

Create successful ePaper yourself

Delete template?

Save as template?