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