Measuring the Price of Anarchy via Perspective Optimization of Unmanned Vehicles in ISR Operations
Abstract
We develop a mixed integer linear program (MILP) to maximize the information gain from a team of autonomous unmanned vehicles (UxVs). Our modeling and algorithmic development enables UxVs operating in a decentralized framework to develop flight plans that simultaneously adapt to the perceived environment and support Intelligence, Surveillance and Reconnaissance (ISR) mission objectives. The mathematical formulation considers each UxV's perspective of the environment and mission, as information is only exchanged when UxVs are part of the same communication network. The main strategy is to discretize space and time to represent the potential information gain. The mathematical program is used to evaluate the "Price of Anarchy": the loss of effectiveness on the system due to the lack of overall coordination of its resources. Network connectivity is represented in the MILP by a set of binary variables. When communication links are added or removed from the problem, the structure of the connectivity matrix permits the identification of sub-networks (i.e., connected components) within the set of UxVs, allowing for an evaluation of system performance with different degrees of decentralization. Our approach is innovative in proposing a "Perspective Optimization" method as well as to measure the "Price of Anarchy" when a team of UxVs performs across multiple mission-centric ISR tasks.
Document Details
- Document Type
- Technical Report
- Publication Date
- Oct 24, 2012
- Accession Number
- ADA581149
Entities
People
- Héctor J. Ortiz-peña
- Mark Karwan
- Michael Hirsch
- Moises Sudit
- Rakesh Nagi
Organizations
- Calspan-University of Buffalo Research Center