Context
As part of the [Epic: RLAIF Reward Function and Model Orchestration Pipeline](#9904), we need a mathematical engine to execute the actual reinforcement learning parameter adjustments across the Native Graph.
Task
Implement the Reward Propagation Engine. This service consumes the success metrics yielded by the Automated Playwright Evaluation Node (#9905) for a given sequence.
Mechanism:
- If the generated Playwright test suite passes (Success): Increase the topological Edge Weight between the
TEST node and the source CLASS node (#9906) and the originating AGENT_MEMORY node, validating the AI's prior conceptual mapping.
- If the generated Playwright test suite crashes/fails (Penalty): Depreciate the corresponding topological Edge Weight. This penalizes hallucinated telemetry or invalid logic and steers future Agent Swarm transversals away from those logic paths.
References
- Origin Session ID:
8f55968e-45d3-4012-ba2f-d1757061e1d2
- Parent Epic: #9904
Context
As part of the [Epic: RLAIF Reward Function and Model Orchestration Pipeline](#9904), we need a mathematical engine to execute the actual reinforcement learning parameter adjustments across the Native Graph.
Task
Implement the Reward Propagation Engine. This service consumes the success metrics yielded by the Automated Playwright Evaluation Node (#9905) for a given sequence.
Mechanism:
TESTnode and the sourceCLASSnode (#9906) and the originatingAGENT_MEMORYnode, validating the AI's prior conceptual mapping.References
8f55968e-45d3-4012-ba2f-d1757061e1d2