【RL】CH2-Bellman equation

the discounted return

Gt=Rt+1+γRt+2+γ2Rt+3+=Rt+1+γ(Rt+2+γRt+3+)=Rt+1+γGt+1

state-value function/the state value of s vπ(s)

vπ(s)=E[GtSt=s]=E[Rt+1+γGt+1St=s]=E[Rt+1St=s]+γE[Gt+1St=s]

Bellman Equation

vπ(s)=E[Rt+1St=s]+γE[Gt+1St=s],=aAπ(as)rRp(rs,a)rmean of immediate rewards +γaAπ(as)sSp(ss,a)vπ(s),mean of future rewards =aAπ(as)[rRp(rs,a)r+γsSp(ss,a)vπ(s)], for all sS.

two equivalent expressions

First

First, it follows from the law of total probability that

p(ss,a)=rRp(s,rs,a),p(rs,a)=sSp(s,rs,a).

Then, equation (2.7) can be rewritten as

vπ(s)=aAπ(as)sSrRp(s,rs,a)[r+γvπ(s)]

Second

Second, the reward r may depend solely on the next state s in some problems. As a result, we can write the reward as r(s) and hence p(r(s)s,a)=p(ss,a), substituting which into (2.7) gives

vπ(s)=aAπ(as)sSp(ss,a)[r(s)+γvπ(s)]

posted @   鸽鸽的书房  阅读(10)  评论(0编辑  收藏  举报
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