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New AI policy 'Cortex' shows promise in Quake gameplay

By PulseAugur Editorial · [1 sources] ·

Researchers have developed Cortex, a compact behavior-cloning policy for the game Quake, utilizing frozen visual features from a DINOv3 encoder. Trained on a subset of the Pixels2Play corpus, Cortex achieved notable progress in gameplay, reaching specific game milestones and securing kills within short episodes. Comparisons with other released models like P2P-150M and NitroGen suggest Cortex's potential, though limitations in sample size and interfaces exist. The study also explored the impact of visual token density and optimization length on performance, identifying covariate shift as a remaining challenge. AI

IMPACT Demonstrates a simpler approach to AI agents in complex environments, potentially reducing computational needs for certain tasks.

RANK_REASON This is a research paper detailing a new AI model for game playing. [lever_c_demoted from research: ic=1 ai=1.0]

Read on arXiv cs.AI →

AI-generated summary · Google Gemini · from 1 sources. How we write summaries →

New AI policy 'Cortex' shows promise in Quake gameplay

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This is a research paper detailing a new AI model for game playing. [lever_c_demoted from research: ic=1 ai=1.0]
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COVERAGE [1]

  1. arXiv cs.AI TIER_1 English(EN) · Dzmitry Malyshau ·

    Cortex: Compact Behavior Cloning for Quake with Frozen Visual Features

    arXiv:2607.22739v1 Announce Type: cross Abstract: We study how far a deliberately simple behavioral-cloning policy can progress in a visually rich first-person game before adding reinforcement learning or explicit memory. Cortex is a compact Quake policy with 10.98 million traina…

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