Research Radar · Experimental implementation
Orchestrator RM
A self-supervised Bradley–Terry reward model for multi-agent orchestration.
What it investigates
Orchestrator RM examines whether automatically generated orchestration traces can train a preference model for more efficient coordination.
Implementation record
The project builds synthetic traces, creates preference pairs using a cost metric, encodes them with a small transformer, fits a Bradley–Terry reward model, and evaluates pairwise rankings. Modules separate trace collection, pair generation, reward modeling, training, and evaluation.
Public record
The linked research item is the public source recorded for this Research Radar build. It provides context for the implementation; this page does not claim to reproduce its results. The repository and its documentation are the current public materials for inspecting the build itself.
Scope and limitations
Synthetic preference pairs encode choices made by the trace generator and cost definition. The page does not claim human-aligned preferences, reliable deployment decisions, or validated improvement in a live multi-agent system.