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What you can do with Awesome AI for Games

A curated, searchable collection of research papers on AI and foundation models across the game lifecycle, organized into six roles.

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Eurekaleo/awesome-ai-for-games on GitHub

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What do you want to do?

4 use cases

  • Build a reading list for LLM game NPC agents

    Collect the Play and Act papers on LLM and RL agents that control game characters.

    View prompt
    Using the Eurekaleo/awesome-ai-for-games README, list the Play and Act papers that involve game NPCs or persona-driven characters, with their paper and code links. Verify that each entry you return appears under the Play and Act heading.

  • Find benchmarks for evaluating LLM agents on games

    Locate benchmark papers such as Orak and VideoGameBench to compare agent evaluations.

    View prompt
    Using the Eurekaleo/awesome-ai-for-games README, list every benchmark paper in the Play and Act section that evaluates LLM or VLM agents on video games. For each one, give the title and paper link, and state whether the README links code for it.

  • Map AI-for-games research across six lifecycle roles

    Use the six-role structure and survey map to plan a research or product review.

    View prompt
    Using the Eurekaleo/awesome-ai-for-games README, summarize the six research roles described in the About the survey section and name the role that covers game testing or support. Verify that your summary uses only the role names and descriptions given in the README.

  • Review bias evaluation methods for game NPC LLMs

    Find the FAIRGAMER paper and related work on social bias in game characters.

    View prompt
    Using the Eurekaleo/awesome-ai-for-games README, list the papers in the Play and Act section that evaluate bias, social behavior, or persona consistency in game agents, with their links. Verify that FAIRGAMER appears in your list.

How to use Awesome AI for Games

  1. Check you have what it needs: A web browser to open the README and the linked survey map and literature search pages; Basic familiarity with the game topic you want to research.
  2. Open Eurekaleo/awesome-ai-for-games on GitHub and read the README and license.
  3. Open the README and jump to the Choose a research role section.
  4. Select the Play and Act role to go to its papers.
  5. Scan the 2026 and 2025 entries for NPC, persona, or social-interaction topics, such as the PUBG Ally and FAIRGAMER entries.
  6. Open the paper and code links for the three to five most relevant entries and save them to your reading list.

These steps come from our top use case, Build a reading list for LLM game NPC agents, which also has a copy-paste agent prompt.

Awesome AI for Games alternatives · Best AI repos for Research

About this repo

Requirements

  • A web browser to open the README and the linked survey map and literature search pages
  • Basic familiarity with the game topic you want to research
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Questions about Awesome AI for Games

What is Awesome AI for Games?

A curated, searchable collection of research papers on AI and foundation models across the game lifecycle, organized into six roles. It is an open-source project on GitHub: https://github.com/Eurekaleo/awesome-ai-for-games.

Who is Awesome AI for Games for?

Written for game researchers, developers, and product teams who need a sorted reading list of AI-for-games papers.

What can I do with Awesome AI for Games?

4 use cases so far, for example: Build a reading list for LLM game NPC agents; Find benchmarks for evaluating LLM agents on games; Map AI-for-games research across six lifecycle roles. Each has steps and a copy-paste agent prompt.

What do I need to run Awesome AI for Games?

A web browser to open the README and the linked survey map and literature search pages; Basic familiarity with the game topic you want to research.

What are alternatives to Awesome AI for Games?

Other hot AI repos in Research: Scientific Agent Skills, Speaker Mem R1, DSH Council, Evo Bot, AI Engineering Course.

Is Awesome AI for Games safe to run?

Deduped does not own, audit or vouch for it. Read the README and license, run it on your own systems first and review every command before you run it.