Understanding System of Systems Development Using an Agent-Based Wave Model

Abstract

System of Systems (SoS) development is a complex process that depends on the cooperation of various independent Systems. SoS acquisition and development differs from that typical for a single System; it has been shown to follow a wave paradigm known as the Wave Model. Agent based models (ABMs) consist of a set of abstracted entities referred to as agents, and a framework using simplified rules for simulating agent decisions and interactions. Agents have their own goals and are capable of perceiving changes in the environment. Systemic (global) behavior emerges from the decisions and interactions of the agents. This research provides a generic model of SoS development with a genetic algorithm and fuzzy assessor implemented in an agent based model. The generic SoS development follows the Wave Model. The genetic algorithm provides an initial SoS metaarchitecture. The fuzzy assessor qualitatively evaluates SoS meta-architectures. The agent-based model implements the generic SoS development, the genetic algorithm, the fuzzy assessor, and independent SoS and system agents and shows the SoS development based on an initial set of conditions. A prototype model is developed to test the concept on a sample from the DoD Intelligence, Surveillance, and Reconnaissance (ISR) domain.

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Document Details

Document Type
Technical Report
Publication Date
Jan 01, 2012
Accession Number
ADA604453

Entities

People

  • Cihan Dagli
  • John Columbi
  • Khaled Haris
  • Louis Pape
  • Nil Kilicay-ergin
  • Paulette Acheson

Tags

Communities of Interest

  • Autonomy

DTIC Thesaurus Topics

  • Acquisition
  • Agent-Based Simulations
  • Algorithms
  • Computer Science
  • Computers
  • Content Addressable Memory
  • Cooperation
  • Department Of Defense
  • Engineering
  • Environment
  • Gap Analysis
  • Genetic Algorithms
  • Simulations
  • System Of Systems
  • Systems Engineering

Readers

  • Agent-Based Social Robotics and Mobile-Assisted Learning in Virtual Environments.
  • Computational Modeling and Simulation
  • Infectious Disease/Epidemiology

Technology Areas

  • AI & ML
  • Biotechnology
  • Biotechnology - Cancer Biotech