Methods › Reinforcement Learning › Value Function Estimation › V-trace
V-trace
Introduced by Lasse Espeholt et al. in IMPALA: Scalable Distributed Deep-RL with Importance Weighted Actor-Learner Architectures
archive 2025-07-28 Description, source and code snippet are the archive's method entry.
V-trace is an off-policy actor-critic reinforcement learning algorithm that helps tackle the lag between when actions are generated by the actors and when the learner estimates the gradient. Consider a trajectory (xₜ, aₜ, rₜ)ᵗ⁼ˢ⁺ⁿₜ₌ₛ generated by the actor following some policy μ. We can define the n-steps V-trace target for V(xₛ), our value approximation at state xₛ as:
vₛ = V(xₛ) + ∑ˢ⁺ⁿ⁻¹ₜ₌ₛγᵗ⁻ˢ(∏ᵗ⁻¹ᵢ₌ₛcᵢ)δₜV
Where δₜV = ρₜ(rₜ + γV(xₜ₊₁) - V(xₜ)) is a temporal difference algorithm for V, and ρₜ = min(ρ̅, (π(aₜ|xₜ))/(μ(aₜ|xₜ))) and cᵢ = min(c̅, (π(aₜ|xₜ))/(μ(aₜ|xₜ))) are truncated importance sampling weights. We assume that the truncation levels are such that ρ̅ ≥c̅.
Papers archive 2025-07-28
30 shown of 34, newest first. Repository counts are the archive's code-links table. A Syntology line states what Syntology ran from that paper's harvested code; it is per sample and not a correctness claim.
-
World Model Agents with Change-Based Intrinsic Motivation 26 Mar 2025 · 1 repository · arXiv:2503.21047
-
Vlearn: Off-Policy Learning with Efficient State-Value Function Estimation 7 Mar 2024 · 0 repositories · arXiv:2403.04453
-
Large Language Models Play StarCraft II: Benchmarks and A Chain of Summarization Approach 19 Dec 2023 · 1 repository · arXiv:2312.11865Syntology ran 2 of 2 samples · 0 unverified · 2 pointer-only (licence)
-
Cleanba: A Reproducible and Efficient Distributed Reinforcement Learning Platform 29 Sep 2023 · 1 repository · arXiv:2310.00036Syntology ran 4 of 8 samples · 4 unverified · 8 pointer-only (licence)
-
A Robust and Opponent-Aware League Training Method for StarCraft II 21 Sep 2023 · 0 repositories
-
AlphaStar Unplugged: Large-Scale Offline Reinforcement Learning 7 Aug 2023 · 1 repository · arXiv:2308.03526Syntology ran 4 of 4 samples · 0 unverified
-
Exploring the Promise and Limits of Real-Time Recurrent Learning 30 May 2023 · 1 repository · arXiv:2305.19044
-
DoMo-AC: Doubly Multi-step Off-policy Actor-Critic Algorithm 29 May 2023 · 0 repositories · arXiv:2305.18501
-
Sharing Lifelong Reinforcement Learning Knowledge via Modulating Masks 18 May 2023 · 2 repositories · arXiv:2305.10997
-
Lifelong Reinforcement Learning with Modulating Masks 21 Dec 2022 · 4 repositories · arXiv:2212.11110
-
AcceRL: Policy Acceleration Framework for Deep Reinforcement Learning 28 Nov 2022 · 0 repositories · arXiv:2211.15023
-
On Efficient Reinforcement Learning for Full-length Game of StarCraft II 23 Sep 2022 · 2 repositories · arXiv:2209.11553Syntology ran 0 of 10 samples · 10 unverified
-
EnvPool: A Highly Parallel Reinforcement Learning Environment Execution Engine 21 Jun 2022 · 3 repositories · arXiv:2206.10558Syntology ran 1 of 5 samples · 4 unverified
-
Semantic Exploration from Language Abstractions and Pretrained Representations 8 Apr 2022 · 0 repositories · arXiv:2204.05080
-
Off-Policy Correction For Multi-Agent Reinforcement Learning 22 Nov 2021 · 1 repository · arXiv:2111.11229Syntology ran 0 of 3 samples · 3 unverified
-
AI in Human-computer Gaming: Techniques, Challenges and Opportunities 15 Nov 2021 · 0 repositories · arXiv:2111.07631
-
A Distributed Deep Reinforcement Learning Technique for Application Placement in Edge and Fog Computing Environments 24 Oct 2021 · 0 repositories · arXiv:2110.12415
-
MACRPO: Multi-Agent Cooperative Recurrent Policy Optimization 2 Sep 2021 · 1 repository · arXiv:2109.00882
-
Rethinking of AlphaStar 7 Aug 2021 · 2 repositories · arXiv:2108.03452
-
An Introduction of mini-AlphaStar 14 Apr 2021 · 1 repository · arXiv:2104.06890
-
Finite-Sample Analysis of Off-Policy Natural Actor-Critic Algorithm 18 Feb 2021 · 0 repositories · arXiv:2102.09318
-
A Lyapunov Theory for Finite-Sample Guarantees of Asynchronous Q-Learning and TD-Learning Variants 2 Feb 2021 · 0 repositories · arXiv:2102.01567
-
Deep Reinforcement Learning with Function Properties in Mean Reversion Strategies 9 Jan 2021 · 1 repository · arXiv:2101.03418
-
TStarBot-X: An Open-Sourced and Comprehensive Study for Efficient League Training in StarCraft II Full Game 27 Nov 2020 · 1 repository · arXiv:2011.13729
-
PFPN: Continuous Control of Physically Simulated Characters using Particle Filtering Policy Network 16 Mar 2020 · 1 repository · arXiv:2003.06959
-
A Self-Tuning Actor-Critic Algorithm 28 Feb 2020 · 0 repositories · arXiv:2002.12928
-
Finite-Sample Analysis of Stochastic Approximation Using Smooth Convex Envelopes 3 Feb 2020 · 0 repositories · arXiv:2002.00874
-
IMPACT: Importance Weighted Asynchronous Architectures with Clipped Target Networks 30 Nov 2019 · 0 repositories · arXiv:1912.00167
-
TorchBeast: A PyTorch Platform for Distributed RL 8 Oct 2019 · 3 repositories · arXiv:1910.03552Syntology ran 4 of 9 samples · 5 unverified · 3 pointer-only (licence)
-
Off-Policy Actor-Critic with Shared Experience Replay 25 Sep 2019 · 0 repositories · arXiv:1909.11583
Tasks archive 2025-07-28
20 shown of 31 tasks the archive attaches to papers tagged with this method, by distinct papers. A task without a page in the catalog is plain text.
Usage over time archive 2025-07-28
Components: the archive holds no method-to-method composition, so PwC's Components table cannot be rebuilt; the Papers list carries no Results column for the same reason (the archive does not join its leaderboard rows to method tags).
Categories archive 2025-07-28
Report a problem or propose a change · a person checks every report against the paper or source before anything changes; decisions are listed on /corrections