Incorporating communication monitoring and control facility in multi-agent systems
Why this work is in the frame
A frame that forgets how it found something cannot be audited. These are the routes that admitted this work.
Bibliographic record
Abstract
In multiple agent computing environments, the communication issue for negotiation, task allocation, etc. is vital for agents to do their tasks. It has been shown that agent systems with many intercommunicating agents can be very difficult to develop without appropriate tools to monitor and mediate communications. Moreover, without agent communication management, the performance of agent systems with large participants may suffer from communication livelocks, deadlock and inconsistency. The objective of this paper is to explore how to improve the multiagent system development process by incorporating a high-level monitoring and control facility into agent communication and distribution environments. A Petri net-based modeling approach is adopted in constructing task-oriented conversation schemata. Conversation managers are deployed into agent daemons throughout the network to provide an environment at network nodes to which agents may be dispatched. An example in an agent-based shop floor is briefly introduced.
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Full frame distilled prediction
Teacher imitationNot calibrated prevalence, not ground truth. Human validation pending. Learned from the 10,348 direct Codex labels and 10,348 direct Gemma labels. Candidate is the union of thresholded teacher heads; consensus is their intersection. These outputs are machine_predicted_unvalidated and are not human labels or direct frontier model labels.
Codex and Gemma teacher scores by category
| Category | Codex | Gemma |
|---|---|---|
| Metaresearch | 0.001 | 0.000 |
| Meta-epidemiology (narrow) | 0.000 | 0.000 |
| Meta-epidemiology (broad) | 0.000 | 0.000 |
| Bibliometrics | 0.000 | 0.000 |
| Science and technology studies | 0.000 | 0.000 |
| Scholarly communication | 0.000 | 0.000 |
| Open science | 0.000 | 0.000 |
| Research integrity | 0.000 | 0.000 |
| Insufficient payload (model declined to judge) | 0.000 | 0.000 |
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 it