SMAC

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

11 leaderboard tables shown for this task, 11 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. 10 shown of 11 until expanded.

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

1 dataset whose archive record lists this task, ordered by the archive's paper count.

Subtasks archive 2025-07-28

2 subtasks in the archive's task tree.

Parent tasks archive 2025-07-28

Most implemented papers archive 2025-07-28

30 shown of 54 papers with code (121 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.
• 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.
• MAVEN: Multi-Agent Variational Exploration
  16 Oct 2019 4 repositories listed Syntology ran 2 of 3 samples · 1 unverified · 2 pointer-only (licence)
  We specifically focus on QMIX [40], the current state-of-the-art in this domain.
• mlrMBO: A Modular Framework for Model-Based Optimization of Expensive Black-Box Functions
  9 Mar 2017 4 repositories listed
  We present mlrMBO, a flexible and comprehensive R toolbox for model-based optimization (MBO), also known as Bayesian optimization, which addresses the problem of expensive black-box optimization by approximating the…
• 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.
• 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.
• Generalizable Agent Modeling for Agent Collaboration-Competition Adaptation with Multi-Retrieval and Dynamic Generation
  20 Jun 2025 1 repository listed
  Adapting a single agent to a new multi-agent system brings challenges, necessitating adjustments across various tasks, environments, and interactions with unknown teammates and opponents.
• Curriculum Learning With Counterfactual Group Relative Policy Advantage For Multi-Agent Reinforcement Learning
  9 Jun 2025 1 repository listed
  Inspired by the success of curriculum learning (CL) in supervised tasks, we propose a dynamic CL framework for MARL that employs an self-adaptive difficulty adjustment mechanism.
• JaxRobotarium: Training and Deploying Multi-Robot Policies in 10 Minutes
  10 May 2025 1 repository listed
  The Multi-Agent RL Benchmark and Learning Environment for the Robotarium (MARBLER) is an exciting recent step in providing a standardized robotics-relevant platform for MARL, by bridging the Robotarium testbed with…
• Learning Generalizable Skills from Offline Multi-Task Data for Multi-Agent Cooperation
  27 Mar 2025 1 repository listed Syntology ran 0 of 1 samples · 1 unverified · 1 pointer-only (licence)
  Secondly, existing works only involve common skills and can not adaptively choose independent knowledge as task-specific skills in each task for fine-grained action execution.
• 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.
• An Extended Benchmarking of Multi-Agent Reinforcement Learning Algorithms in Complex Fully Cooperative Tasks
  7 Feb 2025 1 repository listed Syntology ran 1 of 2 samples · 1 unverified · 2 pointer-only (licence)
  Multi-Agent Reinforcement Learning (MARL) has recently emerged as a significant area of research.
• Dual Ensembled Multiagent Q-Learning with Hypernet Regularizer
  4 Feb 2025 1 repository listed
  Second, we propose a novel hypernet regularizer on hypernetwork weights and biases to constrain the optimization of online global Q-network to prevent overestimation accumulation.
• SMAC-Hard: Enabling Mixed Opponent Strategy Script and Self-play on SMAC
  23 Dec 2024 1 repository listed
  SMAC-HARD supports customizable opponent strategies, randomization of adversarial policies, and interfaces for MARL self-play, enabling agents to generalize to varying opponent behaviors and improve model stability.
• 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…
• A New Approach to Solving SMAC Task: Generating Decision Tree Code from Large Language Models
  21 Oct 2024 1 repository listed
  StarCraft Multi-Agent Challenge (SMAC) is one of the most commonly used experimental environments in multi-agent reinforcement learning (MARL), where the specific task is to control a set number of allied units to…
• Choices are More Important than Efforts: LLM Enables Efficient Multi-Agent Exploration
  3 Oct 2024 1 repository listed Syntology ran 2 of 2 samples · 0 unverified
  With expansive state-action spaces, efficient multi-agent exploration remains a longstanding challenge in reinforcement learning.
• QTypeMix: Enhancing Multi-Agent Cooperative Strategies through Heterogeneous and Homogeneous Value Decomposition
  12 Aug 2024 1 repository listed
  In multi-agent cooperative tasks, the presence of heterogeneous agents is familiar.
• Decentralized Transformers with Centralized Aggregation are Sample-Efficient Multi-Agent World Models
  22 Jun 2024 1 repository listed
  We cast the dynamics learning as an auto-regressive sequence modeling problem over discrete tokens by leveraging the expressive Transformer architecture, in order to model complex local dynamics across different agents…
• Soft-QMIX: Integrating Maximum Entropy For Monotonic Value Function Factorization
  20 Jun 2024 1 repository listed
  In this paper, we propose an enhancement to QMIX by incorporating an additional local Q-value learning method within the maximum entropy RL framework.
• Individual Contributions as Intrinsic Exploration Scaffolds for Multi-agent Reinforcement Learning
  28 May 2024 1 repository listed
  In multi-agent reinforcement learning (MARL), effective exploration is critical, especially in sparse reward environments.
• Efficient Multi-agent Reinforcement Learning by Planning
  20 May 2024 1 repository listed
  Extensive experiments on the SMAC benchmark demonstrate that MAZero outperforms model-free approaches in terms of sample efficiency and provides comparable or better performance than existing model-based methods in…
• PPS-QMIX: Periodically Parameter Sharing for Accelerating Convergence of Multi-Agent Reinforcement Learning
  5 Mar 2024 1 repository listed
  Agents share Q-value network periodically during the training process.
• FoX: Formation-aware exploration in multi-agent reinforcement learning
  22 Aug 2023 1 repository listed
  Recently, deep multi-agent reinforcement learning (MARL) has gained significant popularity due to its success in various cooperative multi-agent tasks.
• HomOpt: A Homotopy-Based Hyperparameter Optimization Method
  7 Aug 2023 1 repository listed
  Traditional methods, like grid search and Bayesian optimization, often struggle to quickly adapt and efficiently search the loss landscape.
• A Unified Framework for Factorizing Distributional Value Functions for Multi-Agent Reinforcement Learning
  4 Jun 2023 1 repository listed
  In fully cooperative multi-agent reinforcement learning (MARL) settings, environments are highly stochastic due to the partial observability of each agent and the continuously changing policies of other agents.
• Robust multi-agent coordination via evolutionary generation of auxiliary adversarial attackers
  10 May 2023 1 repository listed Syntology ran 2 of 5 samples · 3 unverified
  Concretely, to avoid the ego-system overfitting to a specific attacker, we maintain a set of attackers, which is optimized to guarantee the attackers high attacking quality and behavior diversity.
• SMAClite: A Lightweight Environment for Multi-Agent Reinforcement Learning
  9 May 2023 1 repository listed
  The Starcraft Multi-Agent Challenge (SMAC) has been widely used in MARL research, but is built on top of a heavy, closed-source computer game, StarCraft II.
• GHQ: Grouped Hybrid Q Learning for Heterogeneous Cooperative Multi-agent Reinforcement Learning
  2 Mar 2023 1 repository listed
  We firstly define and describe the heterogeneous problems in SMAC.
• Attacking Cooperative Multi-Agent Reinforcement Learning by Adversarial Minority Influence
  7 Feb 2023 1 repository listed
  To achieve maximum deviation in victim policies under complex agent-wise interactions, our unilateral attack aims to characterize and maximize the impact of the adversary on the victims.

Syntology lines on 8 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.