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Related Experiment Video

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Advanced Self-Healing Asphalt Reinforced by Graphene Structures: An Atomistic Insight

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Published on: May 31, 2022

Building adaptive self-healing systems within a resource contested environment.

Brian Phillips¹, Mark Blackburn¹

¹Department of Systems & Enterprises, Stevens Institute of Technology, United States.

|July 22, 2016

Summary

This study introduces a design pattern for self-healing software systems that adapt behavior to survive and win in simulated combat. The adaptive system outperformed 840 non-adapting systems.

Keywords:

Computer science Engineering

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Area of Science:

Software Engineering
Artificial Intelligence
Cognitive Science

Background:

Critical software systems require robust recovery mechanisms for degradation or failure.
A generic methodology for designing self-healing systems is currently lacking in the software engineering community.
Self-healing systems autonomously identify, acquire, and utilize resources for repair and adaptation.

Purpose of the Study:

To investigate a design pattern for creating adaptive self-healing software systems.
To explore how such systems balance actions between healing, movement, and combat in a contested environment.
To evaluate the effectiveness of a cognitive science-inspired multi-system architecture for adaptive behavior.

Main Methods:

Utilized simulated robot tank combat as a challenging environment for the adaptive self-healing system.
Investigated behavior selection strategies for balancing resource acquisition, movement, and combat.
Compared the performance of the adaptive system against 840 non-adapting systems.

Main Results:

The adaptive self-healing system demonstrated effective behavior selection in a resource-contested environment.
The multi-system architecture enabled the system to maximize its ability to win matches and survive.
The study analyzed system characteristics like behavior organization and computer memory utilization.

Conclusions:

A design pattern can facilitate the creation of adaptive self-healing systems.
Cognitive science principles can inform architectures for robust adaptive behavior in critical systems.
Adaptive systems show significant performance advantages over non-adaptive systems in dynamic, contested environments.