Skill UI

This guide provides a comprehensive project management framework for submitting research to the AAAI conference. It maps out every critical milestone, from initial topic selection and abstract submission, through the two-phase peer review, writing the rebuttal, and preparing the final camera-ready version and public artifacts. It emphasizes backward planning from hard deadlines and maintaining evidence integrity throughout the rigorous academic lifecycle.

A comprehensive guide for structuring and writing high-quality AI research manuscripts intended for major academic conferences (e.g., AAAI). It teaches how to structure the first page for maximum impact, clearly state contributions (method, theory, system, etc.), ensure two-column readability, and address ethical limitations to appeal to a broad, non-specialist committee audience.

This guide provides comprehensive instructions for packaging multiagent system (MARL) and game theory evidence for academic submissions, particularly for conferences like AAMAS. It emphasizes that the artifact must be inspectable, containing not just a trained model, but the game definition, environment code, opponent sets, and interaction protocols, ensuring rigorous reproducibility and reviewability.

A comprehensive guide for authors preparing rebuttals following AAMAS preliminary reviews. It details the specific constraints (e.g., double-blind, no new results), the strategies for addressing diverse technical reviewers (such as game theorists, MARL experts, and systems engineers), and the structured pattern required to maximize the impact of a short response window.

A comprehensive guide for authors transitioning an accepted, anonymous conference submission into the final, public camera-ready version for publication. It covers de-anonymization steps, including restoring author details, updating proceedings metadata, reflowing figures for multiagent papers, and integrating rebuttal promises without expanding the core contribution. This ensures adherence to strict publishing standards.

Provides comprehensive guidelines for designing, auditing, and reporting high-rigor multi-agent experiments, especially in game theory and self-play systems. It emphasizes testing the *interaction* claim—such as convergence to equilibrium, truthful behavior, or emergent cooperation—against held-out opponents, populations, and strategic deviations, moving beyond simple single-agent leaderboard scores.

This guide helps authors audit the novelty and eligibility of multiagent system research for submission to AAMAS. It provides comprehensive advice on positioning the work against literature spanning multiple top-tier venues (e.g., NeurIPS, ICML, AAAI, EC, JAAMAS), integrating concepts from multiagent RL, game theory, and social choice. It ensures submissions are positioned accurately compared to the broader academic community, maximizing impact and minimizing rejection risk.

This guide outlines best practices for ensuring rigorous reproducibility of complex interaction claims, especially in game theory and multi-agent systems (MAS). It details required evidence for proofs, experimental setups (agents, opponents, seeds, compute), and consistency checks between the paper's claims and the provided artifacts. Essential for high-stakes academic submissions like AAMAS.

This guide provides a detailed walkthrough of the AAMAS peer review process. It covers everything from initial submissions and technical evaluation (correctness, significance, rigor) to the rebuttal phase, area-chair synthesis, and final decisions. Use this when planning academic submissions or understanding the rigorous criteria for publishing multi-agent systems research.

This comprehensive guide provides a detailed audit checklist for authors submitting to the AAMAS conference. It covers verifying the correct conference track, maintaining double-blind anonymity, adhering to strict formatting rules (e.g., page limits, supplementary zip caps), and identifying potential submission-blocking risks to ensure readiness before the deadline.

Provides comprehensive guidelines for authors preparing supplementary materials for conference submissions (AAMAS). It covers structuring full proofs, extended game definitions, extra experiments, and anonymized code assets, ensuring the main paper remains comprehensible while maximizing the impact of supporting evidence.

A comprehensive guide designed to help researchers determine the optimal conference or journal venue (e.g., AAMAS, NeurIPS, ICML, EC) for multi-agent AI research. It emphasizes that the contribution must center on the interaction result—such as mechanism design, coordination, or negotiation—rather than simply applying a single-agent method in a multiagent testbed. This tool sharpens the research framing before writing begins.