WarpSAC: Towards the Pinnacle of Scalable Off-policy RL by Rethinking Exploration and Exploitation
cs.LG
Submitted: 2026-08-25
Updated: 2026-08-25
Code: https://github.com/wzhhasadream/warprl
Project page: https://wzhhasadream.github.io/WarpSAC
License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/
Terminology
Sources
- Layer Normalization
- For SALE: State-Action Representation Learning for Deep Reinforcement Learning
- Soft Actor-Critic Algorithms and Applications
- TD-MPC2: Scalable, Robust World Models for Continuous Control
- FlashSAC: Fast and Stable Off-Policy Reinforcement Learning for High-Dimensional Robot Control
- Isaac Lab: A GPU-Accelerated Simulation Framework for Multi-Modal Robot Learning
- XQC: Well-conditioned Optimization Accelerates Deep Reinforcement Learning
- HumanoidBench: Simulated Humanoid Benchmark for Whole-Body Locomotion and Manipulation
- ManiSkill3: GPU Parallelized Robotics Simulation and Rendering for Generalizable Embodied AI
- DeepMind Control Suite
- MuJoCo Playground
- mjlab: A Lightweight Framework for GPU-Accelerated Robot Learning
Related papers
- Polynomial-Augmented Neural Networks (PANNs) with Weak Orthogonality Constraints for Enhanced Function and PDE Approximation
- AIRL-S: Unifying Reinforcement Learning and Search-Based Test-Time Scaling via Adversarial Inverse Reinforcement Learning
- Transformers as Bayesian In-Context Experimenters: Smoothness-Adaptive Efficient ATE Estimation
- Convergence issues in Relational Concept Analysis based on AOC-posets
- Beliefs Beyond Posteriors: Local-Consistency Optimisation for Bayesian Neural Networks
- Understanding Diffusion Models via Ratio-Based Function Approximation with SignReLU Networks