Game of Doom

Description from the archive archive 2025-07-28.

Benchmarks archive 2025-07-28

1 leaderboard table shown for this task, 1 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

1 dataset 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

5 shown of 5 papers with code (6 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.
• Agents that Listen: High-Throughput Reinforcement Learning with Multiple Sensory Systems
  5 Jul 2021 1 repository listed
  We are currently in the process of merging the augmented simulator with the main ViZDoom code repository.
• 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 2 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.