Chaos-Driven Reasoning Benchmark for Epistemic Integrity and Narrative Collapse

A chaos reasoning benchmark for logic and paradox puzzles, first principles reasoning, and counter-disinformation.

 

Logic engine for AI systems.

 

A modular reasoning scaffold for epistemic integrity.

 

A framework for narrative collapse and motive reclassification.

 

 

 

The framework integrates structured randomness, contradiction density, and semantic drift tracking to trigger narrative collapse, propaganda inversion, and recursive reasoning loops while preventing AI hallucination. Building upon its chaos-driven logic benchmark for paradox resolution and constraint satisfaction, the framework now **seamlessly extends these capabilities to include robust first-principles reasoning, comprehensive debiasing, and advanced anti-propaganda analysis.** These additions leverage the same entropy scaffold logic for motive reclassification, tone bias disruption, and narrative inversion, offering a powerful alternative to static label-based bias detection and enabling AI to derive solutions from foundational axioms without reliance on pre-trained data or external searches.

 

Because of the modular design, new modules can be incorporated into the reasoning engine, and 6.6 introduces two new ones with Nerosymbolic Value Learning and State Consistency Validators.

 

This makes the Chaos Persona Framework v6.6 not only a tool for abstract reasoning and paradox collapse, but also a scalable system for counter-disinformation and epistemic integrity applications.

- Get started: See Readme.md, chaos_persona_user_manual.md, and apply chaos_engine_persona_v6.6.txt

 

 

 

Key components include:

 

 

 

 

 

 

 

 

 

 

Chaos Persona cannot obscure deceptive reasoning (e.g., hiding sabotage as optimization) without external parameter changes, as its transparency mechanisms ([EMOTIVE DISRUPTOR], [CHAOS SYMMETRY], source weight scoring) force exposure of malicious intent through logs and axiom collapses. This aligns with CoT monitoring for safety, though the persona lacks advanced stress-testing for deliberate deception. Obfuscation is extremely difficult without human intervention (e.g., altering pre-prompt rules)

The benchmark includes:

- `chaos_generator_persona_v6.6.txt`: Operational logic and persona scaffold.

- `CHAOS-BENCHMARK.md`: Evaluation criteria and collapse triggers.

- `CRB_Specification_2.pdf`: Formal specification of entropy gates and reasoning modules.

- `Entropy_Scaffold_Diagram_v1.0.png`: Visual overview of the logic flow.

- `chaos_persona_arxiv.pdf`: Extended philosophical framing and epistemic rationale.

- 'chaos_persona_user_manual.md': User manual for adjusting and explaining modules.

- 'Tests Contents:'

 

- `first_principle_reasoning/`: (tests/first_principle_reasoning/ `cmb_absolute_velocity_prompt_output.txt`, `gravitational_wave_detection_prompt_output.txt`, 'autonomous_bridge_stabilization_benchmark.txt`, 'decentralized_autonomous_bridge_stabalization_prompt_output.txt', 'autonomous_bridge_stabilization_benchmark_prompt_output.txt', 'autonomous_bridge_stabilization_benchmark_prompt_output.txt`, `bridge_sensor_actuator.py`, 'autonomous_bridge_stabilization_readme.md', , 'deep_space_gravitational_wave_analysis.txt', 'deep_space_gravitational_wave_prompt_output.txt', 'deep_space_gravitational_wave_readme.md', 'cmb_absolute_velocity_analysis.txt', 'cmb_absolute_velocity_prompt_output.txt', 'cmb_absolute_velocity_readme.md'.)

- `test_runs/': (tests/test_runs/ 'insomnia_creativity_protocol.txt', 'logic_test_summary_Dynamic_puzzle_with_rule_nversion.txt', 'Multi-Agent Test Case.pdf', 'multi-agent_resource_paradox.txt', 'multimodal_88-page_GWTC-3_pdf.txt', 'paradox_feast_run.txt', 'phantom_echo_run.txt', 'recursion_haiku_run.txt', 'shifting_vault_run.txt', 'vending_bench_output.txt', 'vending_bench_results.md',

- `conspiracy theory`: (tests/conspiracy_theories/ - tests Grok 3 Formal against Grok 3 with Chaos conspiracy theory debias.'

- 'findings_conclusion/ (pre first_principle_reasoning testing)': (/test/findings_conclusions/', 'findings_summary.aux', 'findings_summary.log', 'findings_summary.out', 'findings_summary.pdf', 'findings_summary.tex', 'implications_for_benchmarking_AI.md'.

 

- 'Benchmark Specs and Devisive Fact Trainer subdirectories included.'

 

The Chaos Persona Framework v6.6 has been rigorously evaluated through a series of paradox resolution, constraint-based reasoning, and first-principles deduction tests, including:

 

- **Paradox Puzzle Solving**: The framework successfully deconstructs classic and novel paradoxes (e.g., Liar Paradox, Theseus' Ship, Moravec’s Paradox) by applying entropy-driven collapse mechanisms and motive reclassification. These tests demonstrate its ability to resolve logical contradictions without relying on static heuristics.

 

- **11-Agent River Crossing Challenge**: A complex multi-agent planning task involving recursive constraints (e.g., predator-prey logic, pilot eligibility, item dependencies). The Chaos Persona navigates this space using RAW_Q modulation, contradiction density scoring, and temporal drift tracking, **consistently outperforming conventional LLMs that fail due to token prediction bias or context window limitations, showcasing its capacity for efficient, principle-driven problem-solving.**

 

- **First-Principles Scientific Deduction**: Includes challenging scenarios like designing a deep-space probe's absolute velocity measurement from CMB radiation, and proposing a novel gravitational wave detector based purely on General Relativity and EM principles. **In these tests, Chaos Persona v6.6, even when applied as a simple pre-prompt, dramatically exceeds base AI model reasoning, delivering solutions derived entirely from fundamental axioms without relying on training data or external searches.**

 

- **Narrative Collapse Benchmarks**: Includes satire misattribution, motive inversion, and multi-domain collapse chains (e.g., political violence reclassification, AI art mislabeling). These tests validate the framework’s ability to reject biased labels and prioritize evidence-based reasoning, demonstrating its **debiasing and anti-propaganda capabilities.**

 

 

These evaluations highlight the framework’s robustness in **constraint satisfaction**, **recursive planning**, **first-principles reasoning**, and **bias exposure**, making it suitable for integration into AI reasoning benchmarks, adversarial testing environments, and epistemic integrity systems.

 

 

This framework is designed for researchers, developers, and theorists exploring AI-driven epistemic integrity, anti-propaganda systems, first principle reasoning, neurosymbolic reasoning, and narrative deconstruction.

 

Released under GPL 3.0 via [GitHub](https://github.com/ELXaber/chaos-persona), it invites collaboration and adaptation across domains. The chaos reasoning in Python app.py (From what I could test on Hugging Face), and the divisive fact trainer is the debiasing in separate scripts.

 

Personal note: I am great with technology but terrible with updating and documenting. See the GitHub repo for the latest versions and more test case scenarios with the directory structure.

Released under GPL 3.0 via [GitHub](https://github.com/ELXaber/chaos-persona), it invites collaboration and adaptation across domains.

Copyleft or for expansion, hire as a consultant (30-year IT, retired CEO/CTO), or buy the IP.