siemanko/tensorflow-deepq resource

Health v2 · maintenance only

Flags: no_releases

Adoption not part of the score

1166 stars · 289 forks observed · 2026-08-28

What it is AI-extracted, prompt v1, taxonomy v1, 2026-08-30, confidence not recorded

A Jupyter Notebook-based demonstration of deep Q-learning implemented with TensorFlow, including controllers and simulators that can be combined to train agents in simple game environments. The repository is explicitly marked obsolete in favor of OpenAI Baselines.

Use cases

• learn how deep Q-learning works
• see a reinforcement learning demo in tensorflow
• build a simple RL agent for a toy game
• understand controller and simulator design in RL
• experiment with deep Q networks in notebooks

When to choose

• you want an educational, readable deep Q-learning example
• you are studying older TensorFlow 1.x RL code
• you want a minimal framework to hack on controllers and simulations

When to avoid

• you need a maintained or production-ready RL library
• you want modern TensorFlow or PyTorch support
• you need state-of-the-art RL algorithms - use OpenAI Baselines or Stable Baselines instead

Facets

learning-resource · maturity abandoned

reinforcement-learning machine-learning simulation reinforcement-learning machine-learning deep-learning python deep-q-learning tensorflow jupyter-notebook demonstration obsolete

Member repositories

For agents

markdown · JSON · MCP: product_card(name="siemanko/tensorflow-deepq")