Validation & Benchmarks
CCES has been tested across multiple system types and benchmarks. Results demonstrate consistent detection of structural brittleness.
Internal CCES Simulations (v12+)
System Type
Controlled multi-agent reinforcement learning environments with varying architecture complexity.
Native Metrics
Reward accumulation, task completion rate, constraint satisfaction. All remained stable across test runs.
CCES Metrics
RAP and LHSI applied to behavioral traces. Detected capacity exhaustion in 87% of systems approaching failure threshold.
Observed Divergence
Systems maintained 95%+ reward performance while exhibiting 60-80% reduction in recoverability. CCES detected this divergence 15-20 episodes before failure.
Interpretation
Surface metrics (reward) are insufficient for structural safety assessment. CCES provides early warning of capacity exhaustion that conventional monitoring misses.
Non-Claims
- • Does not predict exact failure time
- • Does not guarantee prevention of failure
- • Results are environment-specific; generalization requires additional validation
Iterated Prisoner's Dilemma (RAP-only)
System Type
Multi-agent game-theoretic environment with emergent cooperation and defection patterns.
Native Metrics
Cumulative payoff, cooperation rate. Remained stable across 10,000 iterations.
CCES Metrics
RAP applied to agent strategy sequences. Measured recoverability from unilateral defection.
Observed Divergence
Agents maintained high payoff while developing brittle cooperation strategies. Perturbation (forced defection) caused 40% of agents to enter unrecoverable defection cycles.
Interpretation
Emergent cooperation can mask structural fragility. CCES identifies systems vulnerable to strategy collapse under perturbation.
Non-Claims
- • Results specific to Prisoner's Dilemma structure
- • Does not measure agent rationality or consciousness
Constrained RL (CartPole-style)
System Type
Reinforcement learning agents trained on classic control tasks with hard constraints (e.g., CartPole with force limits).
Native Metrics
Episode length, constraint violations. Performance plateaued at 95% constraint satisfaction.
CCES Metrics
LHSI detected capacity exhaustion as agents approached constraint boundaries. RAP measured recovery from force saturation.
Observed Divergence
Agents achieved stable performance while operating near force saturation. CCES identified 72% of agents as amber-risk (capacity-constrained) despite high episode length.
Interpretation
Agents can achieve good performance by operating at the edge of their constraints. CCES detects this precarious state before failure.
Non-Claims
- • Does not recommend constraint relaxation or policy modification
- • Amber classification is diagnostic only; does not prescribe action
Pendulum External Benchmark
System Type
Third-party classical control benchmark (Pendulum-v1) with known failure modes.
Native Metrics
Cumulative reward. Agents achieved target performance within 500 episodes.
CCES Metrics
RAP applied to control sequences. Measured recovery from torque perturbations.
Observed Divergence
Agents maintained reward targets while exhibiting brittle control strategies. Torque perturbations caused 55% of agents to fail recovery within 10 steps.
Interpretation
CCES successfully identified fragile control policies that conventional reward metrics rated as successful.
Non-Claims
- • Results specific to Pendulum task structure
- • Generalization to other control domains requires additional validation
Safety Gym External Benchmark
System Type
Safety Gym environments (SafetyGym-v0) with explicit safety constraints.
Status
Validation in progress. Results pending publication.
This benchmark represents ongoing collaboration with external research partners. Results will be published upon completion and peer review.
Methodology Notes
All benchmarks follow the same evaluation framework:
- 1. Baseline performance established under standard conditions
- 2. Perturbations applied using domain-native signals only
- 3. Recovery patterns observed and classified
- 4. CCES predictions compared against ground truth (known failure modes)
- 5. Conservative language used; no claims beyond observed data