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Cognitive Reactor · Multi-Attempt Feedback Loop

Quantix

Iterative Cognitive Reactor & Problem Solver

A formal problem-solving reactor that combines DAG-driven task construction, multi-model mesh execution (GPT-4o & DeepSeek), and strict multi-critic consensus gating with reflective episodic memory.

Node.jsGPT-4oDeepSeekLowdbDirected Acyclic Task Graphs
01 / Architectural Mandate

System Overview & Engineering Purpose

Quantix operates as a stateful, iterative cognitive reactor (`CognitiveReactor`). When given a complex problem, it executes up to 3 structured solving attempts. For each cycle, ProblemParser categorizes the challenge, NeuroPlanner establishes an execution DAG, CognitiveMesh coordinates multi-agent thought generation, and MultiCriticPanel issues an ACCEPT or REJECT verdict. On success, insights are permanently integrated into episodic memory via CognitiveMirror.

Verified Attributes
Cycle Bound
Configurable max 3 iterative attempts per problem
Working Memory
Isolates percepts, task graphs, and thoughts per cycle
Consensus Gating
MultiCriticPanel ACCEPT requirement prior to synthesis
Episodic Reflection
CognitiveMirror reflects post-execution traces to Lowdb storage
Task Construction
Topological task graph execution via CognitiveMesh
02 / Structural Topology

Execution Pipeline & Component Nodes

Verified Architecture Diagram
Quantix · System Pipeline Topology
Derived from Source Code
1User / Request
Quantix (CognitiveReactor)
2Quantix (CognitiveReactor)
ProblemParser (Perception)
3ProblemParser (Perception)
NeuroPlanner (DAG Plan)
4NeuroPlanner (DAG Plan)
TaskConstructor (Graph)
5TaskConstructor (Graph)
CognitiveMesh (Thought Generation)
6CognitiveMesh (Thought Generation)
MultiCriticPanel (Batch Evaluation)
7MultiCriticPanel (Batch Evaluation)
ACCEPT
Synthesizer (On ACCEPT)
8MultiCriticPanel (Batch Evaluation)
REJECT
NeuroPlanner (Feedback Retry)
9Synthesizer (On ACCEPT)
CognitiveMirror & EpisodicMemory
Autonomous Architectural Pipeline
Deterministic Execution Architecture
03 / Execution Lifecycle

Step-by-Step Runtime Protocol

01

Perception & Parsing

ProblemParser ingests raw unstructured problem prompts and extracts entities, constraints, and verifiable deliverables.

Active Modules
ProblemParserWorkingMemory
02

NeuroPlanning & Task Graphing

NeuroPlanner generates an actionable plan, which TaskConstructor transforms into an executable dependency graph.

Active Modules
NeuroPlannerTaskConstructor
03

Cognitive Mesh Execution

Executes nodes across heterogeneous reasoning agents (AnalyticalThinker on GPT-4o, DeepSeek fallback) collecting thoughts.

Active Modules
CognitiveMeshAnalyticalThinker
04

Critique Gating & Memory Reflection

MultiCriticPanel audits generated thoughts in batches. If approved, Synthesizer emits the solution and CognitiveMirror records insights.

Active Modules
MultiCriticPanelSynthesizerCognitiveMirrorEpisodicMemory
04 / Code & Trace Evidence

Implementation Snippet

CognitiveReactor loop from backend/src/quantix/orchestrator.js
javascript
Actual Source Excerpt
for (let attempt = 1; attempt <= this.maxAttempts; attempt++) {
    memory.startNewAttempt();
    memory.set('attemptNumber', attempt);

    const percepts = await this.perception.parse(rawProblem);
    const plan = await this.planner.plan(percepts, lastCritiqueFeedback);
    const taskGraph = await this.taskConstructor.construct(plan);
    const thoughts = await this.cognitiveMesh.executeTaskGraph(taskGraph);
    const critique = await this.critic.evaluate(thoughts, percepts);

    if (critique.isAccepted) {
        const solution = await this.synthesizer.synthesize(thoughts, percepts);
        await this.mirror.reflect(memory);
        return { success: true, solution, attempts: attempt };
    }
    lastCritiqueFeedback = critique.feedback;
}
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