FPS Games

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Most implemented papers archive 2025-07-28

12 shown of 12 papers with code (19 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.

• ViZDoom: A Doom-based AI Research Platform for Visual Reinforcement Learning
  6 May 2016 10 repositories listed Syntology ran 2 of 5 samples · 3 unverified · 5 pointer-only (licence)
  Here, we propose a novel test-bed platform for reinforcement learning research from raw visual information which employs the first-person perspective in a semi-realistic 3D world.
• Playing FPS Games with Deep Reinforcement Learning
  18 Sep 2016 7 repositories listed
  Advances in deep reinforcement learning have allowed autonomous agents to perform well on Atari games, often outperforming humans, using only raw pixels to make their decisions.
• Sample Factory: Egocentric 3D Control from Pixels at 100000 FPS with Asynchronous Reinforcement Learning
  21 Jun 2020 4 repositories listed Syntology ran 0 of 5 samples · 5 unverified
  In this work we aim to solve this problem by optimizing the efficiency and resource utilization of reinforcement learning algorithms instead of relying on distributed computation.
• Counter-Strike Deathmatch with Large-Scale Behavioural Cloning
  9 Apr 2021 2 repositories listed
  This paper describes an AI agent that plays the popular first-person-shooter (FPS) video game `Counter-Strike; Global Offensive' (CSGO) from pixel input.
• BehAVE: Behaviour Alignment of Video Game Encodings
  2 Feb 2024 1 repository listed
  Domain randomisation enhances the transferability of vision models across visually distinct domains with similar content.
• Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games
  27 Sep 2023 1 repository listed
  In this paper, we propose a new approach called Adaptive Behavioral Costs in Reinforcement Learning (ABC-RL) for training a human-like agent with competitive strength.
• AI-enabled Prediction of eSports Player Performance Using the Data from Heterogeneous Sensors
  7 Dec 2020 1 repository listed
  For this reason, we collected the physiological, environmental, and the game chair data from Pro and amateur players.
• Understanding Cyber Athletes Behaviour Through a Smart Chair: CS:GO and Monolith Team Scenario
  18 Aug 2019 1 repository listed
  eSports is the rapidly developing multidisciplinary domain.
• eSports Pro-Players Behavior During the Game Events: Statistical Analysis of Data Obtained Using the Smart Chair
  18 Aug 2019 1 repository listed
  Today's competition between the professional eSports teams is so strong that in-depth analysis of players' performance literally crucial for creating a powerful team.
• Learning-Driven Exploration for Reinforcement Learning
  17 Jun 2019 1 repository listed
  We introduce entropy-based exploration (EBE) that enables an agent to explore efficiently the unexplored regions of state space.
• Active Neural Localization
  24 Jan 2018 1 repository listed
  The results on the 2D environments show the effectiveness of the learned policy in an idealistic setting while results on the 3D environments demonstrate the model's capability of learning the policy and perceptual…
• Deep Successor Reinforcement Learning
  8 Jun 2016 1 repository listed Syntology ran 0 of 1 samples · 1 unverified
  The successor map represents the expected future state occupancy from any given state and the reward predictor maps states to scalar rewards.

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.