We train the policy underpdata(Ot), and want to maxiummaxθEot∼pdata(ot)[logπθ(at|ot))]. But we test the policy underPπθ(Ot). And Pdata(Ot)≠Pπθ(Ot) We have several assumptions: c(st,at)={0ifat=π∗(st)1otherwise that means you will get cost 1 if you make a...
Folders and files Latest commit History44 Commits .vscode hw1 hw2 hw3 hw4 hw5 .gitignore README.md Repository files navigation README Assignments for Berkeley CS 285: Deep Reinforcement Learning, Decision Making, and Control.
This branch is up to date with berkeleydeeprlcourse/homework_fall2023:main.Folders and filesLatest commit vivekmyers update offline dataset to rnd 48ee137· Nov 15, 2023 History42 Commits hw1 Update installation instructions for hw1 Aug 30, 2023 ...