Agentic Collapse

In the paper's words

Abstract The transition from static Large Language Models to dynamic Autonomous Agents has introduced a new class of epistemic failure modes driven by the “Orchestration Penalty”—the factorial increase in verification complexity inherent to multi-step reasoning loops. This research identifies a structural “Latency Killer” in System 2 architectures, where the velocity of agentic action (φ) inherently outpaces the latency of deliberate verification (τ_sys2). We introduce a time-delayed stochastic dynamical system (dφ, dψ, dU) that models the accumulation of “Agentic Drift.” Simulation results reveal a catastrophic phase transition termed “Agentic Collapse,” where a stochastic complexity spike (t ≈ 60) drives the system into an irretrievable high-entropy state before the lagged verifier can compensate.

The abstract, verbatim, and its opening sentence is the claim. Every line below is quoted from the text.

Numbers it reports

1. We introduce a time-delayed stochastic dynamical system ($d\phi, d\psi, dU$) that models the accumulation of “Agentic Drift.” Simulation results reveal a catastrophic phase transition termed “Agentic Collapse,” where a stochastic complexity spike ($t \approx 60$) drives the system into an irretrievable high-entropy state before the lagged verifier can compensate.

   from A

2. We demonstrate that perfect stability is mathematically impossible in open-ended agentic loops; instead, safety requires a regime of “Metastability” enforced by a “Popperian Guillotine” —a discrete safety interlock that resets the agent when epistemic potential exceeds a critical threshold ($U_{crit}=0.88$).

   from A

3. Guillotine Threshold ($U_{crit}=0.88$): Provides a distinct ceiling for the system’s tolerance of uncertainty.

   from 3.2 Parameter Selection

4. Collapse At $t=62.85$, the Epistemic Potential reached $0.9102$, breaching the critical safety threshold of $0.88$.

   from 4.5 Anatomy of an Agentic

How it is done

1. Finally, we derive an “Epistemic Speed Limit,” arguing that robust autonomy requires dynamically throttling execution speed to match the “Cost of Thought.” Keywords: Agentic AI; System 2 Reasoning; Neuro-Symbolic Integration; Delay Differential Equations; AI Safety; Popperian Falsifiability; Cybernetic Control Theory.

   from A

2. This approach has yielded significant improvements in mathematical and coding benchmarks, suggesting that the models are capable of genuine problem-solving.

   from 1.2 The System 2

3. Current regulations rely on the concept of a “locked” algorithm, but locking an agent deprives it of its primary value: adaptability.

   from 1.6 Regulatory

4. To rigorously model the stability of autonomous AI systems, we define the internal state of the agent as a dynamic vector evolving over time.

   from 2.1 The Agentic State Vector

What would falsify it

1. Finally, we derive an “Epistemic Speed Limit,” arguing that robust autonomy requires dynamically throttling execution speed to match the “Cost of Thought.” Keywords: Agentic AI; System 2 Reasoning; Neuro-Symbolic Integration; Delay Differential Equations; AI Safety; Popperian Falsifiability; Cybernetic Control Theory.

   from A

2. In this paradigm, models do not merely predict the next token; they formulate plans, execute tools, and observe results in a continuous cycle.

   from 1.1 From

3. Epistemology in Autonomous Loops The deployment of autonomous agents in high-stakes environments necessitates a return to normative epistemology, specifically the requirement for automated falsifiability.

   from 1.4 Normative

Where the claim stops

1. In this paradigm, models do not merely predict the next token; they formulate plans, execute tools, and observe results in a continuous cycle.

   from 1.1 From

2. However, this recursive structure also introduces the risk of error propagation.

   from 1.1 From

3. The system relies on the assumption that the model’s reasoning capabilities are robust enough to recover from these deviations.

   from 1.1 From

Where to read

1. 1. INTRODUCTION1,430 words · 6 min
2. 2. THEORETICAL FRAMEWORK623 words · 3 min
3. 3. METHODOLOGY165 words · 1 min
4. 4. RESULTS139 words · 1 min
5. STATE: SYSTEM_2_STABILITY. Semantic Fluency stabilized at106 words · 1 min
6. CRITICAL: AGENTIC_COLLAPSE, was a systemic failure of the79 words · 1 min
7. 5. DISCUSSION198 words · 1 min
8. APPENDICES8 words · 1 min
9. WARNING: SYSTEM_2_LAG_DRAG |8 words · 1 min
10. STATE: SYSTEM_2_STABILITY |8 words · 1 min
11. CRITICAL: AGENTIC_COLLAPSE |8 words · 1 min