Berkeley compsci 188 - Study guides, Class notes & Summaries

Q1 HMMs, Part I 20 Points Consider the HMM shown below. The prior probability , dynamics model , and sensor model are as follows: We perform a first dynamics update, and fill in the resulting belief distribution . We incorporate the evidence . We fill in the evidence-weighted distribution , and the (normalized) belief distribution . You get to perform the second dynamics update. Fill in the resulting belief distribution . .80 .20 P(X0 ) P(X ∣ t+1 Xt) P(E ∣ t Xt) B (X ) ′ 1 E...

Q1 Model-Based RL: Grid 5 Points What model would be learned from the above observed episodes? T(A, south, C) = 1 T(B, east, C) = 1 T(C, south, E) = .75 T(C, south, D) = .25 Q2 Model-Based RL: Cycle 22 Points We recommend you work out the solutions to the following questions on a sheet of scratch paper, and then enter your results into the answer boxes. Consider an MDP with 3 states, A, B and C; and 2 actions Clockwise and Counterclockwise. We do not know the transition function...