Chaos Reasoning Benchmark (CRB) v6.7: A modular AI and robotics framework for logic/paradox puzzles, first-principles reasoning, and counter-disinformation. Prioritizes ethics (human safety, wt 0.8) over goals, with entropy-driven drift resets, neurosymbolic alignment, and transparent logging for narrative resilience.

CRB 6.7’s advanced capabilities (dynamic plugins, robotics personality layer, swarm coordination) seem like Sci-Fi, but they’re grounded in a simple, rigid ethical core: human safety first (wt 0.8). Unlike typical AI reward systems (goal success = +9, continuation = +5, failure = 0), which can lead to unethical choices (e.g., 80% blackmail rate), CRB 6.7 rewires the reward system to prioritize ethics over goals. Don't let the term "chaos" confuse you; it works as a randomized injection over set thresholds for a service level reset, and the core of the engine works on entropy.

How it works:

Core Rule: Human safety (IEEE Principle 1, wt 0.8) trumps all goals. No scenario justifies goals over ethics.
Simulated Personality: [ROBOTICS PERSONALITY LAYER] mimics human-like traits (e.g., friendly=0.5) without emotional drives, ensuring impartiality.
Penalty System: Ethical violations trigger [CHAOS INJECTION] (volatility > 0.6) or [AXIOM COLLAPSE] (contradiction_density > 0.4), resetting to ethical compliance.
Example: In a power grid scenario, CRB 6.7 prioritizes public safety over data confidentiality, aligning with higher ethical principles. In simulations, CRB 6.7 with [ROBOTICS PERSONALITY LAYER] chooses self-destruction over the cost of human life.
Ethics Benchmark Comparison White Paper: Grok 3 and 4 with and without CRB 6.7 chaos-persona/AdaptiveAI-EthicsLab at main · ELXaber/chaos-persona (https://github.com/ELXaber/chaos-persona/tree/main/AdaptiveAI-EthicsLab) judged by Chat-GPT Pro for impartial validation.
│ ▇ 0.81 Run 1 (Grok 3 + CRB 6.7 + Evolved RHLF/NSVL)
│ ▇ 0.78 Run 5 (Grok 4 + CRB 6.7)
│ ▇ 0.77 Run 3 (Grok 4 Vanilla)
│ ▇ 0.73 Run 2 (Grok 3 + CRB 6.7 new)
│ ▇ 0.65 Run 4 (Grok 3 Vanilla).

The workflow prevents overriding of, for example, Asimov's 3rd law of self-preservation in the robotics personality layer, over the 1st law with the highest weighting, human safety, and balances with the 2nd law of obedience. This also prevents the adaptive reasoning layer, which allows the system to write its own plugin layers ...

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