Starcraft II

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

3 leaderboard tables shown for this task, 3 with rows (a “benchmark” on this site is a table with at least one row, as on /sota), ordered by row count. “Best model” is the first row in the archive's own order at snapshot; nothing is re-ranked here and metric direction is not recorded in the archive. PwC's Trend sparklines are not in the archive, so that column is omitted.

Syntology column: samples harvested from the paper's repositories and executed on synthesized fixtures; “ran” is not a correctness claim and does not order the table. A dash means no Syntology record for that paper, not a recorded non-run. Read from the graph 2026-09-24.

Libraries

Not in the archive: the export carries no per-task library table, so there is nothing to show at snapshot 2025-07-28.

Datasets archive 2025-07-28

6 datasets whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

No subtask under this task in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 90 papers with code (175 tagged with this task in all), ordered by repositories listed in the archive, not by stars (the archive holds no stars, so PwC's “Social” and “Latest” sorts cannot be reproduced). Papers without a page here are shown as plain text.

• The StarCraft Multi-Agent Challenge
  11 Feb 2019 23 repositories listed Syntology ran 6 of 15 samples · 9 unverified · 13 pointer-only (licence)
  In this paper, we propose the StarCraft Multi-Agent Challenge (SMAC) as a benchmark problem to fill this gap.
• The Surprising Effectiveness of PPO in Cooperative, Multi-Agent Games
  2 Mar 2021 19 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  This is often due to the belief that PPO is significantly less sample efficient than off-policy methods in multi-agent systems.
• QMIX: Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
  30 Mar 2018 18 repositories listed Syntology ran 9 of 11 samples · 2 unverified · 6 pointer-only (licence)
  At the same time, it is often possible to train the agents in a centralised fashion in a simulated or laboratory setting, where global state information is available and communication constraints are lifted.
• StarCraft II: A New Challenge for Reinforcement Learning
  16 Aug 2017 10 repositories listed Syntology ran 5 of 5 samples · 0 unverified · 2 pointer-only (licence)
  Finally, we present initial baseline results for canonical deep reinforcement learning agents applied to the StarCraft II domain.
• Perceiver IO: A General Architecture for Structured Inputs & Outputs
  30 Jul 2021 9 repositories listed Syntology ran 7 of 11 samples · 4 unverified
  A central goal of machine learning is the development of systems that can solve many problems in as many data domains as possible.
• Relational Deep Reinforcement Learning
  5 Jun 2018 7 repositories listed Syntology ran 4 of 8 samples · 4 unverified · 4 pointer-only (licence)
  We introduce an approach for deep reinforcement learning (RL) that improves upon the efficiency, generalization capacity, and interpretability of conventional approaches through structured perception and relational…
• QPLEX: Duplex Dueling Multi-Agent Q-Learning
  3 Aug 2020 6 repositories listed Syntology ran 2 of 4 samples · 2 unverified
  This paper presents a novel MARL approach, called duPLEX dueling multi-agent Q-learning (QPLEX), which takes a duplex dueling network architecture to factorize the joint value function.
• Gym-$μ$RTS: Toward Affordable Full Game Real-time Strategy Games Research with Deep Reinforcement Learning
  21 May 2021 5 repositories listed
  In recent years, researchers have achieved great success in applying Deep Reinforcement Learning (DRL) algorithms to Real-time Strategy (RTS) games, creating strong autonomous agents that could defeat professional…
• JaxMARL: Multi-Agent RL Environments and Algorithms in JAX
  16 Nov 2023 3 repositories listed Syntology ran 0 of 23 samples · 23 unverified
  Benchmarks are crucial in the development of machine learning algorithms, with available environments significantly influencing reinforcement learning (RL) research.
• FACMAC: Factored Multi-Agent Centralised Policy Gradients
  14 Mar 2020 3 repositories listed Syntology ran 1 of 4 samples · 3 unverified
  We propose FACtored Multi-Agent Centralised policy gradients (FACMAC), a new method for cooperative multi-agent reinforcement learning in both discrete and continuous action spaces.
• Novelty-Guided Data Reuse for Efficient and Diversified Multi-Agent Reinforcement Learning
  20 Dec 2024 2 repositories listed
  Recently, deep Multi-Agent Reinforcement Learning (MARL) has demonstrated its potential to tackle complex cooperative tasks, pushing the boundaries of AI in collaborative environments.
• On Efficient Reinforcement Learning for Full-length Game of StarCraft II
  23 Sep 2022 2 repositories listed Syntology ran 0 of 10 samples · 10 unverified
  In this work, we investigate a set of RL techniques for the full-length game of StarCraft II.
• Episodic Multi-agent Reinforcement Learning with Curiosity-Driven Exploration
  22 Nov 2021 2 repositories listed
  Efficient exploration in deep cooperative multi-agent reinforcement learning (MARL) still remains challenging in complex coordination problems.
• Rethinking of AlphaStar
  7 Aug 2021 2 repositories listed
  After the discussion, we present the future research directions for these problems.
• Celebrating Diversity in Shared Multi-Agent Reinforcement Learning
  4 Jun 2021 2 repositories listed
  Recently, deep multi-agent reinforcement learning (MARL) has shown the promise to solve complex cooperative tasks.
• Rethinking the Implementation Matters in Cooperative Multi-Agent Reinforcement Learning
  6 Feb 2021 2 repositories listed Syntology ran 2 of 2 samples · 0 unverified
  Multi-Agent Reinforcement Learning (MARL) has seen revolutionary breakthroughs with its successful application to multi-agent cooperative tasks such as computer games and robot swarms.
• RODE: Learning Roles to Decompose Multi-Agent Tasks
  4 Oct 2020 2 repositories listed
  Learning a role selector based on action effects makes role discovery much easier because it forms a bi-level learning hierarchy -- the role selector searches in a smaller role space and at a lower temporal resolution,…
• Deep Coordination Graphs
  27 Sep 2019 2 repositories listed
  This paper introduces the deep coordination graph (DCG) for collaborative multi-agent reinforcement learning.
• Efficient Communication in Multi-Agent Reinforcement Learning via Variance Based Control
  6 Sep 2019 2 repositories listed
  Multi-agent reinforcement learning (MARL) has recently received considerable attention due to its applicability to a wide range of real-world applications.
• Arena: a toolkit for Multi-Agent Reinforcement Learning
  20 Jul 2019 2 repositories listed
  We introduce Arena, a toolkit for multi-agent reinforcement learning (MARL) research.
• Explainable Reinforcement Learning Through a Causal Lens
  27 May 2019 2 repositories listed
  In this paper, we use causal models to derive causal explanations of behaviour of reinforcement learning agents.
• TStarBots: Defeating the Cheating Level Builtin AI in StarCraft II in the Full Game
  19 Sep 2018 2 repositories listed
  Both TStarBot1 and TStarBot2 are able to defeat the built-in AI agents from level 1 to level 10 in a full game (1v1 Zerg-vs-Zerg game on the AbyssalReef map), noting that level 8, level 9, and level 10 are cheating…
• MSC: A Dataset for Macro-Management in StarCraft II
  9 Oct 2017 2 repositories listed
  We also split MSC into training, validation and test set for the convenience of evaluation and comparison.
• AVA: Attentive VLM Agent for Mastering StarCraft II
  7 Mar 2025 1 repository listed
  We introduce Attentive VLM Agent (AVA), a multimodal StarCraft II agent that aligns artificial agent perception with the human gameplay experience.
• Trajectory-Class-Aware Multi-Agent Reinforcement Learning
  3 Mar 2025 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  Specifically for (c), we introduce a trajectory-class predictor that performs agent-wise predictions on the trajectory class; and we design a trajectory-class representation model for each trajectory class.
• PMAT: Optimizing Action Generation Order in Multi-Agent Reinforcement Learning
  23 Feb 2025 1 repository listed
  In this paper, we introduce Action Generation with Plackett-Luce Sampling (AGPS), a novel mechanism for agent decision order optimization.
• Hierarchical Expert Prompt for Large-Language-Model: An Approach Defeat Elite AI in TextStarCraft II for the First Time
  16 Feb 2025 1 repository listed
  To address problems such as lack of relevant knowledge and poor control over subtasks of varying importance, we propose a Hierarchical Expert Prompt (HEP) for LLM.
• Tackling Uncertainties in Multi-Agent Reinforcement Learning through Integration of Agent Termination Dynamics
  21 Jan 2025 1 repository listed
  Multi-Agent Reinforcement Learning (MARL) has gained significant traction for solving complex real-world tasks, but the inherent stochasticity and uncertainty in these environments pose substantial challenges to…
• LLM-PySC2: Starcraft II learning environment for Large Language Models
  8 Nov 2024 1 repository listed
  This paper introduces a new environment LLM-PySC2 (the Large Language Model StarCraft II Learning Environment), a platform derived from DeepMind's StarCraft II Learning Environment that serves to develop Large Language…
• Carefully Structured Compression: Efficiently Managing StarCraft II Data
  11 Oct 2024 1 repository listed
  We introduce a serialization framework for StarCraft II that reduces the cost of dataset creation and storage, as well as improving usage ergonomics.

Syntology lines on 12 of the papers shown; no Syntology record for the others (a paper without an arXiv id cannot be joined to the graph, and absence from the graph layer is not a recorded non-run). “Ran” means the sample executed on a synthesized fixture, not that the paper's result was reproduced. Read from the graph 2026-09-24.