class MDP extends AnyRef
The MDP
class provides Markov Decision Processes.
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new
MDP(t: Tensor3D, r: Tensor3D, g: Double = 0.9, thr: Double = 1E-4)
- t
the transitional conditional probability t(s1, a, s2) = P(s2 | s1, a), where s1, s2 in S, a in A
- r
the reward tensor r(s1, a, s2)
- g
the discount factor in (0, 1)
- thr
the threshold (stop when v changes little)
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def
getPi: VectoI
Return the optimal policy, i.e., the best action for each state.
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def
optimize: (VectoD, MatriD)
Determine optimal values for the state value function 'v' and the state-action value function 'q'.
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