Proceedings of the 2013 international conference on Autonomous agents and multi-agent systems
Bibliographic record
Abstract
The Autonomous Agents and MultiAgent Systems (AAMAS) conference series brings together researchers from around the world to share the latest advances in the field. It provides a highprofile and high-quality forum for research in the theory and practice of autonomous agents and multiagent systems. AAMAS 2002, the first of the series, was held in Bologna, followed by Melbourne (2003), New York (2004), Utrecht (2005), Hakodate (2006), Honolulu (2007), Estoril (2008), Budapest (2009), Toronto (2010), Taipei (2011), and Valencia (2012). You are now about to enter the proceedings of AAMAS 2013, held in Saint Paul, Minnesota, in May 2013. In addition to the general track for the AAMAS 2013 conference, submissions were invited to four special tracks: robotics, virtual agents, innovative applications, and (new this year) a special challenges and visions track. The aims of these special tracks were to give researchers from these areas a strong focus, to provide a forum for discussion and debate within the encompassing structure of AAMAS, and to ensure that the impact of both theoretical contributions and innovative applications were recognized. The tracks were chaired by leaders in the corresponding fields: Daniele Nardi and Monica Nicolescu for the robotics track, Stefan Kopp and Catherine Pelachaud for the virtual agents track, Bo An and John Thangarajah for the innovative applications track, and Jeff Rosenschein for the challenges and visions track. The special track chairs provided critical input to selection of Program Committee (PC) and Senior Program Committee (SPC) members, and to the reviewer allocation and the review process itself. Both full paper and extended abstract submissions were solicited for AAMAS 2013. The papers were selected by means of a thorough review and discussion process which included an opportunity for authors to respond to reviewer comments, a discussion phase between SPC members and (track/PC) chairs, after which the program chairs made the final decisions. In the general track, 13 papers were withdrawn that were accepted as extended abstracts. No other papers were withdrawn after notification. Each full paper was allocated 8 pages in the proceedings, challenges and visions papers were allocated 4 pages, and extended abstracts 2 pages. Oral presentations were allocated 20 minutes in the program. Both full papers and extended abstracts were presented as posters during the conference. Of the submissions, 383 (64%) were indicated as being student papers, which indicates that AAMAS continues to be a nurturing environment for students. Submissions were assigned keywords, each of which was classified under one of 15 top-level topics (e.g., Cooperation). Representation of top-level topics (measured by first keyword) was broad, with top counts in the areas of Economic Paradigms (201 submissions), Agent Cooperation (137), Agent Reasoning (111), Learning and Adaptation (100), and Robotics (94).
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How this classification was reachedexpand
Full frame machine prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. The Gemma side is a direct model label for every work in the frame, read from the title-only record. The Codex side is a classifier learned from the 10,348 direct Codex labels and calibrated to design-weighted sample rates; fields without enough sample support carry no Codex call. Candidate is the union of the two sides; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels.
Distilled classifier scores by category (both heads)
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.002 | 0.006 |
| Meta-epidemiology (narrow) | 0.001 | 0.000 |
| Meta-epidemiology (broad) | 0.002 | 0.001 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.001 | 0.001 |
| Scholarly communication | 0.007 | 0.003 |
| Open science | 0.002 | 0.002 |
| Research integrity | 0.002 | 0.003 |
| Insufficient payload (model declined to judge) | 0.059 | 0.022 |
Machine scores (provisional)
The two teacher heads of the student model, read on this work. A score orders the frame for review; it never asserts a category, and the validation status ships verbatim with every row.
Baseline scores from an immature model (maturity gate not passed, 7 training rounds). Scores rank; they never assert a category.
score_only:v0-immature-baseline · verbatim from the scoring run: score_only means the number may rank works, and no category label ships from itClassification
machine, unvalidatedMachine predicted; a candidate call from one source (direct Gemma or distilled Codex), not a consensus.
How this classification was reached, model by model and score by score, is at the end of the page under "How this classification was reached".