STRATON-LLM
Design Decisions
This project is shaped by a series of deliberate architectural choices. The goal is not only to make the system work, but to make the reasoning process inspectable, extensible, and trustworthy.
Separate negotiation from the base MAS framework
The negotiation system is implemented as a standalone module so it can evolve independently, remain testable, and be reused across different agent frameworks later.
Use a finite-state protocol engine
A protocol engine makes the dialogue inspectable and constrains invalid moves. This avoids fragile free-form multi-turn exchanges that are difficult to debug or evaluate.
Persist accepted mappings in a mapping store first
The system stores successful alignments separately before touching source ontologies. This keeps ontology evolution controlled and auditable.
Always evaluate the agreement after the dialogue
The framework does not assume the latest answer is correct. Agreement must pass confidence thresholds and post-dialogue heuristics before acceptance.
Keep LLMs inside bounded responsibilities
LLMs assist matching, proposal generation, and argument reasoning, but protocol control, persistence, and evaluation remain explicit engineered components.
Avoid direct ontology mutation during negotiation
Negotiation outcomes are stored as mappings first. Controlled ontology versioning happens later as a separate, auditable step.
Trade-off map
Protocol control over free-form chat
Gain
Higher trust, better observability, easier replay and evaluation.
Cost
More implementation effort and stricter conversation design.
Mapping store before ontology updates
Gain
Safer evolution and reversible outcomes.
Cost
Adds one more persistence layer to manage.
Heuristic agreement scoring
Gain
Reduces weak or biased acceptances.
Cost
Requires extra tuning and scenario-based validation.
LLM assistance within explicit modules
Gain
Keeps reasoning flexible without losing system boundaries.
Cost
Requires interface discipline and prompt guardrails.
STRATON-LLM pages
Overview
Problem framing, project goals, research contribution, and end-to-end system story.
Architecture
Six-layer architecture, module boundaries, and system walkthrough.
Protocol & Negotiation
Triggering, dialogue acts, FSM control, and a worked negotiation scenario.
Design Decisions
The major choices, trade-offs, and constraints that shaped STRATON-LLM.
Evaluation & Learning
Agreement trust, heuristic scoring, persistence, and evolution roadmap.
Design posture
- → Prefer explicit control over magical behavior.
- → Keep negotiation evidence auditable.
- → Treat trust and learning as system responsibilities.
- → Use LLM capability, but do not surrender architecture to it.