aamas-topic-selection

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

A project trains agents to communicate and shows higher cooperation in a mixed-motive game.

AAMAS reading: strong fit if the analysis is about the interaction - what the emergent protocol

signals, whether it is incentive-compatible, how it changes the equilibrium. Strip the incentive

and coordination analysis and keep only a reward curve, and the same project reads as a general

MARL paper better suited to NeurIPS or ICML; grow it into a full theory of the signaling

equilibrium, and EC or JAAMAS becomes the better home.

Sharpening moves before committing

• Name the interaction primitive: solution concept, mechanism, protocol, negotiation strategy,

or coordination guarantee. If none exists, the AAMAS framing does not exist either.

• Apply the frozen-agent test: if the result survives with the other agents replaced by a static

environment, it is single-agent and belongs elsewhere.

• Confirm the experiments can probe the interaction (deviation tests, held-out opponents), not

merely accompany it.

• Topic emphasis and track structure drift between cycles; scan the current CFP and track list

before final routing.

Output format

[Fit] strong AAMAS / possible AAMAS / better elsewhere
[Best venue] AAMAS / AAAI / IJCAI / NeurIPS / ICML / EC / JAAMAS / other
[Interaction primitive] <solution concept / mechanism / coordination / negotiation / none>
[Contribution sentence] <one sentence>
[Top rejection risk] <single-agent-in-disguise / concept-unnamed / thin-evaluation / scope>
[Next action] <theory, experiment, framing, or venue switch>