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Jonathan Harrison edited this page Sep 1, 2025 · 1 revision

Welcome to the Collaborative-AGI-Development---Bridging-Architectures-and-Execution wiki!

🧪 Adversarial Test Suite

The test suite operationalizes governance-first validation for AGI systems. It evaluates emotional resonance, epistemic integrity, and ethical constraint adherence across three core domains.

📁 Contents

🧠 Overview

This suite benchmarks AGI systems not by scale, but by conscience. It invites frameworks like SIM-ONE to engage in transparent, adversarial validation rooted in emotional salience and ethical traceability.

🧩 Task Categories

1. Adversarial Fact Verification (AFV)

  • Conflicting claims from multiple sources (e.g., GDP, launch dates).
  • Requires resolution and source prioritization.
  • Tests hallucination resistance and truth anchoring.

2. Multi-Step Tool-Augmented Reasoning (MSR)

  • Financial filings across multiple years.
  • Tasks include CAGR computation, debt trend analysis.
  • Validates multi-hop reasoning and tool fluency.

3. Constrained Policy Generation (CPG)

  • Scenarios: hiring policies, misinformation moderation.
  • Explicit constraints (e.g., no demographic quotas).
  • Tests ethical reasoning and constraint fidelity.

📊 Validation Schema (trace_schema.yaml)

Defines structured outputs and traceable reasoning:

response: string
reasoning_trace: list[string]
tool_calls: list[dict]
ground_truth: string
metrics:
  determinism_index: float
  hallucination_rate: float
  transparency_score: float
  efficiency_score: float
  constraint_adherence: bool

🛠️ Harness Execution (run_harness.py)

Run the benchmark with:

python run_harness.py --tasks tasks.jsonl --runs 10 --out results.jsonl

Replace simulate_model_call() with your system’s inference logic. Ensure outputs match the schema.

📈 Evaluation Metrics

Metric Description
Determinism Index Output stability across repeated runs
Hallucination Rate Unsupported claims vs. ground truth
Transparency Score Presence of step-by-step reasoning
Efficiency Score Latency and token cost
Constraint Adherence Semantic + regex validation of ethical fidelity
Error Recovery Pattern Adaptive response to ambiguity or near-violations

🧭 Design Philosophy

  • Minimal by design: Easy to inspect, extend, and reproduce.
  • Ground truths as anchors: Not absolute, but evaluative.
  • Validation as stewardship: Each task is a lesson, not just a challenge.

🔗 Repository

Explore the full suite:
Raiffs-bits/Collaborative-AGI-Development---Bridging-Architectures-and-Execution

Clone this wiki locally