ERAM Repository, Burak Oktenli

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eram-simulation.html	ERAM v1.0 Escalation Risk Assessment Model	Mar 31, 2026
LICENSE	All Rights Reserved · Proprietary	Mar 31, 2026

eram-simulation.html 672 lines · 86KB

  1<!DOCTYPE html>
  2<html lang="en">
  3<head>
  4<title>ERAM v1.0</title>
  5
  6/* ERAM: Escalation Risk Assessment Model
  7 * for AI-Enabled Command and Control
  8 * Author: Burak Oktenli
  9 * Georgetown University
 10 * MPS Applied Intelligence
 11 */
 12
 13// Full source: 672 lines

README.md

ERAM: Escalation Risk Assessment Model for AI-Enabled Command and Control

ERAM is a quantitative cross-domain escalation risk framework for authority-governed autonomous systems. It monitors decision compression, cascade propagation, and escalation probability across interconnected multi-domain command nodes in real time, enabling governance architectures to enforce deliberation windows before actions cascade across domain boundaries. ERAM computes five core metrics, Decision Compression Ratio (DCR), Authority Chain Integrity (ACI), Cascade Risk Index (CRI), Escalation Probability P(esc), and Human Recovery Window (HRW), from node-level governance parameters and inter-node coupling coefficients.

Publication Status

Published on SSRN · ID: 6176802.
Author: Burak Oktenli
Affiliation: Georgetown University, M.P.S. Applied Intelligence
Status: Published on SSRN · ID: 6176802, interactive simulation live.

Key Features

Decision Compression Ratio (DCR)
Authority Chain Integrity: ACI = τ × (A/3) × f × (1-P_d)
Cascade Risk Index (CRI) modeling cross-domain governance degradation propagation
Escalation Probability P(esc) with DCR-weighted domain risk computation
Human Recovery Window (HRW) quantifying remaining human intervention time
6 cross-domain scenarios (Flash War, AV, Maritime, Infrastructure, DEF→CIV, HOTL)
600 Monte Carlo runs with seeded PRNG (Mulberry32, 0x4F7A2C1E)
FLAME integration for deliberation-window-based escalation reduction
5-tab interface: Escalation, Monte Carlo, Analysis, Audit, Live 3D Demo

Technical Specifications

Language: HTML, JavaScript, CSS (single-file architecture)
Dependencies: Three.js r128 (3D topology visualization)
Runtime: Browser-based, client-side only
Lines of code: 672

Author

Burak Oktenli
Georgetown University, M.P.S. Applied Intelligence
ORCID: 0009-0001-8573-1667
Contact: info@burakoktenli.com

License

Copyright © 2026 Burak Oktenli · Georgetown University M.P.S. Applied Intelligence · ORCID 0009-0001-8573-1667 · Washington, DC · CC BY 4.0. Viewing and personal evaluation permitted. Commercial use, modification, and redistribution prohibited without written consent.