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

TL;DR

This paper proposes Energentic Intelligence, a new class of autonomous systems focused on self-sustenance through internal energy regulation, moving beyond reward-driven paradigms to enable persistent operation in resource-volatile environments.

Contribution

It introduces a formal energy-based utility framework and a modular architecture for autonomous agents that self-regulate energy and thermal states, demonstrated through simulation.

Findings

Emergence of stable, resource-aware behavior in simulation

Viability-constrained survival horizon guides autonomous behavior

Energy-based utility function enables self-sustaining operation

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.