Ross ROSS = Recommend OSS · open-source software intelligence for agents

wangshusen/DRL resource

Deep Reinforcement Learning observed · 2026-08-28

github.com/wangshusen/DRL · NOASSERTION (other) observed · 2026-08-28

Health v2 · maintenance only

32/100

  • Activity 0
  • Release rhythm 35
  • Longevity 100

Flags: no_releases no_license

How is this computed?

round(0.45*activity + 0.35*rhythm + 0.20*longevity); archived -> min(score, 10) — computed 2026-09-02. Adoption (stars, forks) is never an input.

  • gap_med: n/a
  • age_days: 2236
  • days_rel: n/a
  • days_push: 1362
  • n_releases_24m: 0

Full methodology

Adoption not part of the score

4685 stars · 677 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-29, confidence not recorded

A collection of lecture slides, notes, and videos on deep reinforcement learning by Wang Shusen, covering TD learning, DQN, policy gradients, and actor-critic methods. It is educational course material rather than software.

Use cases

  • learn deep reinforcement learning from scratch
  • understand Q-learning and DQN algorithms
  • study policy gradient and actor-critic methods
  • find lecture slides on TD learning
  • prepare a reinforcement learning course

When to choose

  • you want structured educational material on DRL fundamentals
  • you prefer slide-based learning with accompanying videos
  • you need concise explanations of DQN, A2C, and TRPO

When to avoid

  • you need a ready-to-use RL library or codebase
  • you want hands-on coding exercises
  • you need content in English only

Facets

learning-resource · maturity stable

machine-learning reinforcement-learning documentation reinforcement-learning machine-learning tutorials cross-platform deep-reinforcement-learning lecture-slides course-material chinese-videos

1 source

Member repositories

RepositoryRoleHealth v2
wangshusen/DRLmain32

For agents

markdown · JSON · MCP: product_card(name="wangshusen/DRL")

Data as of 2026-08-30T08:39:29.467469+00:00 · Report a problem