rail-berkeley / design-bench
☆48Updated 2 years ago
Alternatives and similar repositories for design-bench:
Users that are interested in design-bench are comparing it to the libraries listed below
- ☆22Updated 2 years ago
- Baselines for Model-Based Optimization☆51Updated 3 years ago
- Official pytorch implementation for our ICLR 2023 paper "Latent State Marginalization as a Low-cost Approach for Improving Exploration".☆24Updated last year
- ☆29Updated 2 years ago
- [AutoML'22] Bayesian Generational Population-based Training (BG-PBT)☆26Updated 2 years ago
- Code to accompany the paper "Mismatched No More: Joint Model-Policy Optimization for Model-Based RL"☆21Updated 3 years ago
- Revisiting Peng's Q(lambda) for Modern Reinforcement Learning☆16Updated 3 years ago
- Invariant Causal Prediction for Block MDPs☆44Updated 4 years ago
- Experiment for Understanding the Effects of Dataset Characteristics on Offline Reinforcement Learning☆24Updated 2 years ago
- IV-RL - Sample Efficient Deep Reinforcement Learning via Uncertainty Estimation☆38Updated 3 months ago
- PyTorch implementation of Probabilistic Network Ensembles on toy problems☆23Updated last year
- 🔍 Codebase for the ICML '20 paper "Ready Policy One: World Building Through Active Learning" (arxiv: 2002.02693)☆18Updated last year
- Benchmarks for Model-Based Optimization☆84Updated 9 months ago
- Estimating Q(s,s') with Deep Deterministic Dynamics Gradients☆32Updated 4 years ago
- ☆41Updated last year
- ☆32Updated 6 months ago
- Implementation of Tactical Optimistic and Pessimistic value estimation☆24Updated last year
- Official implementation for the paper "Offline Meta RL - Identifiability Challenges and Effective Data Collection Strategies", NeurIPS 20…☆30Updated 3 years ago
- Clean, extensible implementation of MACAW [ICML 2021]☆13Updated 3 years ago
- This code implements Prioritized Level Replay, a method for sampling training levels for reinforcement learning agents that exploits the …☆85Updated 3 years ago
- Learning Action-Value Gradients in Model-based Policy Optimization☆31Updated 3 years ago
- Model-Based Reinforcement Learning via Latent-Space Collocation.☆32Updated last year
- Code accompanying the paper "Information Directed Reward Learning for Reinforcement Learning" (NeurIPS 2021).☆13Updated 3 years ago
- ☆29Updated 3 years ago
- Code for the paper Novelty Search in Representational Space for Sample Efficient Exploration presented at NeurIPS 2020.☆14Updated 6 months ago
- implementation of Wasserstein Natural Policy Gradients and Wasserstein Natural Evolution Strategies☆11Updated 3 years ago
- Official code repo for paper: Hybrid RL: Using both offline and online data can make RL efficient.☆24Updated last year
- ☆28Updated 3 years ago
- Meta-Learning Acquisition Functions for Transfer Learning in Bayesian Optimization☆35Updated 4 years ago
- Conservative Q learning in Jax☆52Updated last year