Proceedings of the 25th Workshop "From Objects to Agents"
Bibliographic record
Abstract
The Workshop "From Objects to Agents" (WOA) is the reference event for Italian researchers active in the Agents and Multi-Agent Systems research domain.It has been held every year since 2000, and this year WOA reaches its 25-year anniversary.For this special occasion, the workshop has been held in a very exclusive location the Forte di Bard in Valle d'Aosta.The workshop took place from 8 th to 10 th July, during which 22 original papers have been presented.To commemorate the anniversary, the workshop has also included a Dissemination Track inviting papers recently appeared on international conferences and journals:10 papers were presented in this track.Overall, more than 50 researchers from all Italy have attended the workshop.The "Fabio Bellifemine" keynote speech was given by Amit Chopra (Lancaster University), who discussed the topic "Communication Meaning: Why Multiagent Abstractions Are Foundational to Software Systems Research".In his discussion, the speaker started from a thorny question for the WOA community: After three decades of work on enabling flexible interactions between agents, has the research on the agent-based paradigm failed to mature in software engineering solutions actually used outside the academic world?The speaker shed a light on a possible solution to realize the promise of modeling meaning in interaction protocols, and how this addresses thorny, longstanding problems in systems, including in fields such as networks, distributed systems, and programming languages.These advances put multiagent abstractions at the heart of systems research and raise deep and novel research questions.
Fetched live from OpenAlex and de-inverted. Abstracts are not stored in this database: the inverted indexes are 8.6 GB of the frame’s 9.3 GB of text, and the host has 13 GB free.
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 | 0.006 | 0.008 |
| Meta-epidemiology (narrow) | 0.001 | 0.001 |
| Meta-epidemiology (broad) | 0.001 | 0.002 |
| Bibliometrics | 0.001 | 0.001 |
| Science and technology studies | 0.002 | 0.002 |
| Scholarly communication | 0.010 | 0.008 |
| Open science | 0.003 | 0.005 |
| Research integrity | 0.003 | 0.005 |
| Insufficient payload (model declined to judge) | 0.099 | 0.046 |
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".