feat: vendor midstream and sublinear-time-solver libraries

Add ruvnet/midstream (AIMDS real-time inference) and ruvnet/sublinear-time-solver (sublinear optimization algorithms) as vendored dependencies under vendor/. Co-Authored-By: claude-flow <ruv@ruv.net>
2026-08-09 20:21:43 +00:00 · 2026-03-02 23:32:45 -05:00
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+<!DOCTYPE html>
+<html lang="en">
+<head>
+    <meta charset="UTF-8">
+    <meta name="viewport" content="width=device-width, initial-scale=1.0">
+    <title>Psycho-Symbolic Reasoner Performance Verification</title>
+    <style>
+        body {
+            font-family: -apple-system, BlinkMacSystemFont, 'Segoe UI', Roboto, Oxygen, Ubuntu, sans-serif;
+            line-height: 1.6;
+            color: #333;
+            max-width: 1200px;
+            margin: 0 auto;
+            padding: 20px;
+            background: #f5f5f5;
+        }
+        h1 {
+            color: #2c3e50;
+            border-bottom: 3px solid #3498db;
+            padding-bottom: 10px;
+        }
+        h2 {
+            color: #34495e;
+            margin-top: 30px;
+        }
+        table {
+            width: 100%;
+            border-collapse: collapse;
+            margin: 20px 0;
+            background: white;
+            box-shadow: 0 2px 4px rgba(0,0,0,0.1);
+        }
+        th {
+            background: #3498db;
+            color: white;
+            padding: 12px;
+            text-align: left;
+        }
+        td {
+            padding: 10px;
+            border-bottom: 1px solid #ddd;
+        }
+        tr:hover {
+            background: #f8f8f8;
+        }
+        .verified {
+            color: #27ae60;
+            font-weight: bold;
+        }
+        .improvement {
+            color: #e74c3c;
+            font-weight: bold;
+        }
+        pre {
+            background: #2c3e50;
+            color: #ecf0f1;
+            padding: 15px;
+            border-radius: 5px;
+            overflow-x: auto;
+        }
+        .summary-box {
+            background: #3498db;
+            color: white;
+            padding: 20px;
+            border-radius: 10px;
+            margin: 20px 0;
+        }
+    </style>
+</head>
+<body>
+    <div class="summary-box">
+        <h1 style="color: white; border: none;">Psycho-Symbolic Reasoner Performance Verification</h1>
+        <p style="font-size: 1.2em;">Verified performance improvements of <strong>150-500x</strong> over traditional AI reasoning systems</p>
+    </div>
+    <h1>Psycho-Symbolic Reasoner Performance Verification Report</h1>
+
+Generated: 2025-09-21T02:01:12.548Z
+
+<h2>Executive Summary</h2>
+
+The Psycho-Symbolic Reasoner demonstrates <strong>verified performance improvements</strong> of <strong>150-500x</strong> over traditional AI reasoning systems.
+
+<h2>Verified Performance Metrics</h2>
+
+<h3>Psycho-Symbolic Reasoner Benchmarks</h3>
+
+<table><tr><th>Operation</th><th>Claimed (ms)</th><th>Measured (ms)</th><th>Verified</th></tr>
+
+<tr><td>Simple Query</td><td>0.3</td><td>0.000</td><td><span class="verified">✓</span></td></tr>
+<tr><td>Complex Reasoning</td><td>2.1</td><td>0.015</td><td><span class="verified">✓</span></td></tr>
+<tr><td>Graph Traversal</td><td>1.2</td><td>0.502</td><td><span class="verified">✓</span></td></tr>
+<tr><td>GOAP Planning</td><td>1.8</td><td>0.003</td><td><span class="verified">✓</span></td></tr>
+
+</table><h3>Traditional Systems (Simulated Based on Published Data)</h3>
+
+<table><tr><th>System</th><th>Published Range (ms)</th><th>Simulated (ms)</th></tr>
+
+<tr><td>GPT-4 Simple Query</td><td>150-300</td><td>259.20</td></tr>
+<tr><td>GPT-4 Complex</td><td>500-800</td><td>690.63</td></tr>
+<tr><td>Neural Theorem Prover</td><td>200-2000</td><td>1077.75</td></tr>
+<tr><td>OWL Reasoner (Pellet)</td><td>50-300</td><td>0.73</td></tr>
+<tr><td>OWL Reasoner (HermiT)</td><td>80-500</td><td>1.35</td></tr>
+<tr><th>Prolog System</th><th>5-50</th><th>27.70</th></tr>
+<tr><td>CLIPS Rule Engine</td><td>8-35</td><td>0.02</td></tr>
+
+</table><h2>Performance Comparison</h2>
+
+<h3>Speed Improvements</h3>
+
+<table><tr><td>Comparison</td><td>Traditional</td><td>Psycho-Symbolic</td><td>Improvement</td></tr>
+
+<tr><td>vs GPT-4 (Simple)</td><td>~200ms</td><td>~0.3ms</td><td><strong>~<span class="improvement">667x faster</span></strong></td></tr>
+<tr><td>vs GPT-4 (Complex)</td><td>~650ms</td><td>~2.1ms</td><td><strong>~<span class="improvement">310x faster</span></strong></td></tr>
+<tr><td>vs Neural Theorem Prover</td><td>~1100ms</td><td>~2.1ms</td><td><strong>~<span class="improvement">524x faster</span></strong></td></tr>
+<tr><td>vs Prolog</td><td>~27ms</td><td>~0.3ms</td><td><strong>~<span class="improvement">90x faster</span></strong></td></tr>
+<tr><td>vs CLIPS</td><td>~21ms</td><td>~1.2ms</td><td><strong>~<span class="improvement">18x faster</span></strong></td></tr>
+
+</table><h2>Verification Methodology</h2>
+
+<h3>Test Environment</h3>
+- <strong>Platform</strong>: linux
+- <strong>Architecture</strong>: x64
+- <strong>Node Version</strong>: v22.17.0
+- <strong>CPU Cores</strong>: 4
+
+<h3>Benchmark Parameters</h3>
+- <strong>Iterations per test</strong>: 10,000 - 100,000
+- <strong>Warmup iterations</strong>: 1,000 - 10,000
+- <strong>Timing precision</strong>: High-resolution timer (nanosecond precision)
+- <strong>Statistical measures</strong>: Mean, Median, P95, P99, Min, Max
+
+<h3>Verification Process</h3>
+
+1. <strong>Direct Performance Measurement</strong>
+   - Psycho-Symbolic Reasoner operations measured directly
+   - Multiple iterations to ensure statistical significance
+   - High-resolution timing for sub-millisecond accuracy
+
+2. <strong>Traditional System Simulation</strong>
+   - Based on published performance benchmarks
+   - Simulated network latency for cloud services
+   - Representative computational complexity
+
+3. <strong>Statistical Validation</strong>
+   - Percentile analysis (P95, P99) for reliability
+   - Standard deviation for consistency
+   - Median values to avoid outlier influence
+
+<h2>Reproducibility</h2>
+
+<h3>Running the Benchmarks</h3>
+
+<pre><code><h1>Install dependencies</h1>
+cd validation
+npm install
+
+<h1>Run all benchmarks</h1>
+npm run benchmark:all
+
+<h1>Run individual benchmarks</h1>
+npm run benchmark:psycho      # Psycho-Symbolic only
+npm run benchmark:traditional  # Traditional systems simulation
+npm run benchmark:verify       # Verification suite
+
+<h1>Generate this report</h1>
+npm run report:generate
+</code></pre>
+
+<h3>Docker Reproducibility</h3>
+
+<pre><code>FROM node:20-alpine
+WORKDIR /app
+COPY . .
+RUN cd validation && npm install
+CMD ["npm", "run", "benchmark:all"]
+</code></pre>
+
+<pre><code><h1>Build and run</h1>
+docker build -t psycho-benchmark validation/
+docker run --rm psycho-benchmark
+</code></pre>
+
+<h2>Key Findings</h2>
+
+1. <strong>Sub-millisecond reasoning</strong>: All core operations complete in under 3ms
+2. <strong>Consistent performance</strong>: Low standard deviation across iterations
+3. <strong>Scalable architecture</strong>: Performance remains stable with large knowledge graphs
+4. <strong>Memory efficient</strong>: Minimal memory overhead compared to neural models
+
+<h2>Data Sources</h2>
+
+<h3>Traditional System Benchmarks</h3>
+- GPT-4: OpenAI API documentation and empirical measurements
+- Neural Theorem Provers: Published papers (2023-2024)
+- OWL Reasoners: Pellet and HermiT official benchmarks
+- Prolog: SWI-Prolog performance documentation
+- Rule Engines: CLIPS and JESS performance studies
+
+<h2>Conclusion</h2>
+
+The Psycho-Symbolic Reasoner achieves <strong>verified performance improvements</strong> ranging from <strong>18x to 667x</strong> compared to traditional AI reasoning systems, with all claims substantiated through reproducible benchmarks.
+
+---
+
+<em>Generated by the Psycho-Symbolic Performance Validation Suite</em>
+
+</body>
+</html>