Dota 2

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Most implemented papers archive 2025-07-28

13 shown of 13 papers with code (27 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.

• Proximal Policy Optimization Algorithms
  20 Jul 2017 188 repositories listed Syntology ran 99 of 176 samples · 77 unverified · 94 pointer-only (licence)
  We propose a new family of policy gradient methods for reinforcement learning, which alternate between sampling data through interaction with the environment, and optimizing a "surrogate" objective function using…
• An Empirical Model of Large-Batch Training
  14 Dec 2018 11 repositories listed Syntology ran 0 of 6 samples · 6 unverified
  In an increasing number of domains it has been demonstrated that deep learning models can be trained using relatively large batch sizes without sacrificing data efficiency.
• Beyond the Meta: Leveraging Game Design Parameters for Patch-Agnostic Esport Analytics
  29 May 2023 2 repositories listed
  Therefore, the proposed methodology for representing characters can increase the life-spam of machine learning models as well as contribute to a higher performance when compared to traditional techniques typically…
• 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.
• Context-Aware Toxicity Detection in Multiplayer Games: Integrating Domain-Adaptive Pretraining and Match Metadata
  2 Apr 2025 1 repository listed
  The detrimental effects of toxicity in competitive online video games are widely acknowledged, prompting publishers to monitor player chat conversations.
• Towards Detecting Contextual Real-Time Toxicity for In-Game Chat
  20 Oct 2023 1 repository listed
  Real-time toxicity detection in online environments poses a significant challenge, due to the increasing prevalence of social media and gaming platforms.
• Semantic HELM: A Human-Readable Memory for Reinforcement Learning
  15 Jun 2023 1 repository listed
  Then we feed these tokens to a pretrained language model that serves the agent as memory and provides it with a coherent and human-readable representation of the past.
• Joint action loss for proximal policy optimization
  26 Jan 2023 1 repository listed
  Instead, for each sub-action we calculate the loss separately, which is less prone to clipping during updates thereby making better use of samples.
• Machine learning models for DOTA 2 outcomes prediction
  3 Jun 2021 1 repository listed
  Prediction of the real-time multiplayer online battle arena (MOBA) games' match outcome is one of the most important and exciting tasks in Esports analytical research.
• TLeague: A Framework for Competitive Self-Play based Distributed Multi-Agent Reinforcement Learning
  25 Nov 2020 1 repository listed
  This poses non-trivial difficulties for researchers or engineers and prevents the application of MARL to a broader range of real-world problems.
• Dota 2 with Large Scale Deep Reinforcement Learning
  13 Dec 2019 1 repository listed Syntology ran 0 of 9 samples · 9 unverified
  On April 13th, 2019, OpenAI Five became the first AI system to defeat the world champions at an esports game.
• Time to Die: Death Prediction in Dota 2 using Deep Learning
  21 May 2019 1 repository listed
  Even though death events are rare within a game (1\% of the data), the model achieves 0.
• Real-time eSports Match Result Prediction
  10 Dec 2016 1 repository listed
  In this paper, we try to predict the winning team of a match in the multiplayer eSports game Dota 2.

Syntology lines on 3 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.