Starcraft

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

No benchmark for this task in the archive.

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

8 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 148 papers with code (311 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.
• Is Independent Learning All You Need in the StarCraft Multi-Agent Challenge?
  18 Nov 2020 7 repositories listed
  Most recently developed approaches to cooperative multi-agent reinforcement learning in the \emph{centralized training with decentralized execution} setting involve estimating a centralized, joint value function.
• 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…
• Counterfactual Multi-Agent Policy Gradients
  24 May 2017 7 repositories listed Syntology ran 1 of 1 samples · 0 unverified · 1 pointer-only (licence)
  COMA uses a centralised critic to estimate the Q-function and decentralised actors to optimise the agents' policies.
• 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…
• Stabilising Experience Replay for Deep Multi-Agent Reinforcement Learning
  28 Feb 2017 5 repositories listed
  Many real-world problems, such as network packet routing and urban traffic control, are naturally modeled as multi-agent reinforcement learning (RL) problems.
• Weighted QMIX: Expanding Monotonic Value Function Factorisation for Deep Multi-Agent Reinforcement Learning
  18 Jun 2020 4 repositories listed
  We show in particular that this projection can fail to recover the optimal policy even with access to Q^*, which primarily stems from the equal weighting placed on each joint action.
• 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.
• Learning when to Communicate at Scale in Multiagent Cooperative and Competitive Tasks
  23 Dec 2018 3 repositories listed Syntology ran 1 of 11 samples · 10 unverified
  Learning when to communicate and doing that effectively is essential in multi-agent tasks.
• Towards Accurate Generative Models of Video: A New Metric & Challenges
  3 Dec 2018 3 repositories listed
  To this extent we propose Fr\'{e}chet Video Distance (FVD), a new metric for generative models of video, and StarCraft 2 Videos (SCV), a benchmark of game play from custom starcraft 2 scenarios that challenge the…
• 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.
• Value-based CTDE Methods in Symmetric Two-team Markov Game: from Cooperation to Team Competition
  21 Nov 2022 2 repositories listed
  In this paper, we identify the best learning scenario to train a team of agents to compete against multiple possible strategies of opposing teams.
• 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.
• Multi-Agent Collaboration via Reward Attribution Decomposition
  16 Oct 2020 2 repositories listed
  In this work, we propose Collaborative Q-learning (CollaQ) that achieves state-of-the-art performance in the StarCraft multi-agent challenge and supports ad hoc team play.
• 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,…
• Learning to Play No-Press Diplomacy with Best Response Policy Iteration
  8 Jun 2020 2 repositories listed Syntology ran 0 of 7 samples · 7 unverified
  It also features a large combinatorial action space and simultaneous moves, which are challenging for RL algorithms.
• Randomized Entity-wise Factorization for Multi-Agent Reinforcement Learning
  7 Jun 2020 2 repositories listed Syntology ran 0 of 4 samples · 4 unverified
  Multi-agent settings in the real world often involve tasks with varying types and quantities of agents and non-agent entities; however, common patterns of behavior often emerge among these agents/entities.
• 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.

Syntology lines on 15 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.