pathak22/noreward-rl
noreward-rl
[ICML 2017] TensorFlow code for Curiosity-driven Exploration for Deep Reinforcement Learning
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Community Evaluation
“Academic reference implementation with historical significance but effectively unmaintained and not suitable for active development”
Pros
- ✓1479 stars indicates significant community interest in curiosity-driven exploration research
- ✓Implements ICML 2017 published research with TensorFlow, providing academic credibility
- ✓Focused niche tool for a specific RL exploration problem rather than bloated general framework
- ✓Python-based making it accessible to ML researchers and practitioners
Cons
- ✕Zero contributors and 0% community health score suggests abandoned maintenance and no active development
- ✕No README summary, problem statement, or documentation available indicates poor project setup
- ✕0% issue close rate with unknown test coverage and CI/CD suggests no quality assurance infrastructure
- ✕TensorFlow 1.x era codebase (ICML 2017) likely incompatible with modern TensorFlow 2.x without significant refactoring
Best for
Researchers studying curiosity-driven exploration in deep RL who need reference implementation of the ICML 2017 paper
Avoid if
You need production-ready code, active maintenance, or integration with modern RL frameworks
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- Apr 18, 2026
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