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기본적으로 Deepmind X UCL 의 강의자료를 쫓아갑니다!
Lecture 1 - introduction.pdf
4 MiB
Lecture 2- Exploration and control_slides.pdf
822.9 KiB
Lecture 3 - MDPs and Dynamic Programming.pdf
916.3 KiB
Lecture 4 - Theoretical Fundamentals of DP Algorithms.pdf
692.6 KiB
Lecture 5 - ModelFreePrediction.pdf
1.3 MiB
Lecture 6 - Model-free control.pdf
728.3 KiB
위의 두개 자료에서 필요없는 내용 있어서 아래 자료 사용하기로 함
lecture-4-model-free-prediction-.pdf
1.4 MiB
lecture-5-model-free-control-.pdf
1.4 MiB
Lecture 7- Function approximation in reinforcement learning .pdf
1.1 MiB
Lecture 8 - Model Based Reinforcement Learning.pdf
1.2 MiB
Lecture 9- Policy gradients and actor critics.pdf
616.6 KiB
Lecture 10- Approximate Dynamic Programming.pdf
415.7 KiB
Lecture 11- Off-policy and multi-step.pdf
412.9 KiB
Lecture 12- Deep RL 1 .pdf
3.3 MiB
Lecture 13 - Deep RL 2.pdf
1.3 MiB
ac_dpg.pdf
231.2 KiB
trpo_ppo.pdf
3.1 MiB
sac.pdf
1.1 MiB