English

Energentic Intelligence: From Self-Sustaining Systems to Enduring Artificial Life

Artificial Intelligence 2025-06-06 v1 Machine Learning Systems and Control Systems and Control

Abstract

This paper introduces Energentic Intelligence, a class of autonomous systems defined not by task performance, but by their capacity to sustain themselves through internal energy regulation. Departing from conventional reward-driven paradigms, these agents treat survival-maintaining functional operation under fluctuating energetic and thermal conditions-as the central objective. We formalize this principle through an energy-based utility function and a viability-constrained survival horizon, and propose a modular architecture that integrates energy harvesting, thermal regulation, and adaptive computation into a closed-loop control system. A simulated environment demonstrates the emergence of stable, resource-aware behavior without external supervision. Together, these contributions provide a theoretical and architectural foundation for deploying autonomous agents in resource-volatile settings where persistence must be self-regulated and infrastructure cannot be assumed.

Keywords

Cite

@article{arxiv.2506.04916,
  title  = {Energentic Intelligence: From Self-Sustaining Systems to Enduring Artificial Life},
  author = {Atahan Karagoz},
  journal= {arXiv preprint arXiv:2506.04916},
  year   = {2025}
}
R2 v1 2026-07-01T03:01:15.406Z