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