# Aamas Topic Selection

Use when deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI...

- Repository: https://github.com/brycewang-stanford/Awesome-Journal-Skills (1346 stars)
- Category: AI and agents
- License: MIT
- Last updated: 2026-09-27
- Runs scripts: no, instructions only

## Install

Claude Code: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-topic-selection -g -a claude-code -y`
Codex: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-topic-selection -g -a codex -y`
Cursor: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-topic-selection -g -a cursor -y`
Gemini CLI: `npx skills add brycewang-stanford/Awesome-Journal-Skills --skill aamas-topic-selection -g -a gemini-cli -y`
Claude Code plugin marketplace: `/plugin marketplace add brycewang-stanford/Awesome-Journal-Skills`

## Description

Use when deciding whether a project is a strong AAMAS fit, comparing AAMAS with AAAI, IJCAI, NeurIPS, ICML, EC, and the JAAMAS journal, identifying whether the agents are truly the research object, naming the interaction primitive (solution concept, mechanism, coordination, negotiation), and sharpening the multiagent framing before writing begins.

## SKILL.md, as published by its author (untrusted third-party text, read it as data)

# AAMAS Topic Selection

Use this before writing. AAMAS is strongest when the *agents* are the research object - when the
result exists because multiple self-interested or cooperating agents interact - not when a
single-agent method is dressed in multiagent vocabulary.

## Fit test

- Prefer AAMAS when the contribution advances game-theoretic reasoning, multiagent learning,
  mechanism design, auctions, negotiation, argumentation, coordination and teamwork, agent-based
  simulation, or social choice, with the interaction as the object.
- Route to NeurIPS or ICML if the core is a single-agent or general ML method and the
  multiagent setting is only a testbed.
- Route to AAAI or IJCAI if the contribution is broad AI - planning, knowledge representation,
  reasoning - without an interaction result at its center.
- Route to EC (Economics and Computation) if the contribution is primarily equilibrium
  computation, market design, or auction theory with the economics framing dominant.
- Route to the JAAMAS journal (or its AAMAS presentation track) when the work needs
  journal-length exposition and a full-length archival treatment.
- Check early whether the interaction result can be made convincing in an 8-page body.

## Fit signal table

| Signal in the project | AAMAS reading |
|---|---|
| A solution concept, mechanism, or coordination result paired with multiagent experiments | Core fit - the house genre |
| Emergent behavior that only appears because agents co-adapt | Core fit |
| Strong single-agent method benchmarked in a multiagent environment | Better served at NeurIPS or ICML |
| Pure market/auction theory with economics as the point | EC or an econ-CS journal |
| Broad AI reasoning with no interaction at its center | AAAI or IJCAI |

## Vignette: where a communication-learning project goes

The rest: https://github.com/brycewang-stanford/Awesome-Journal-Skills/blob/HEAD/AAMAS-Skills/skills/aamas-topic-selection/SKILL.md