Evolutionary algorithms in theory and practice: evolution strategies, evolutionary programming, genetic algorithms
Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back
Designing Autonomous Agents: Theory and Practice from Biology to Engineering and Back
Genetic Algorithms in Search, Optimization and Machine Learning
Genetic Algorithms in Search, Optimization and Machine Learning
Test and Evaluation by Genetic Algorithms
IEEE Expert: Intelligent Systems and Their Applications
Generating Software Test Data by Evolution
IEEE Transactions on Software Engineering
A multi-objective approach to search-based test data generation
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Applying particle swarm optimization to software testing
Proceedings of the 9th annual conference on Genetic and evolutionary computation
Constraint-based Evolutionary Testing of Autonomous Distributed Systems
ICSTW '08 Proceedings of the 2008 IEEE International Conference on Software Testing Verification and Validation Workshop
Unmanned and autonomous systems mission based test and evaluation
PerMIS '09 Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems
A fast and elitist multiobjective genetic algorithm: NSGA-II
IEEE Transactions on Evolutionary Computation
Modeling and convergence analysis of distributed coevolutionary algorithms
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
Modeling and simulation for unmanned and autonomous system test and evaluation
PerMIS '09 Proceedings of the 9th Workshop on Performance Metrics for Intelligent Systems
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A DoD mission and challenge is to enable a high percentage of autonomous vehicles in the warfighter fleet by 2015. These systems will need to display a high degree of autonomous capabilities. The capabilities of these autonomous systems must be acceptable to the warfighter and his/her logistical support structure. Autonomous systems of the future will need to be tested so their mission capabilities and robustness are predictable to the warfighter. The principal challenge therefore is the set of test strategies for these future autonomous systems. The goal of the test community is that these autonomous systems be broadly accepted to seamlessly operate either independently or as part of a human-in-the-loop system. Our goal is to develop an efficient intelligent test process that will enable the rapid introduction of autonomous systems on the battlefield. We propose a novel war game simulation-based multi-objective evolutionary test framework that combines the elements of testing an autonomous system's mission execution capabilities as a function of its innate capabilities and evolutionary computation.