Open Access. Powered by Scholars. Published by Universities.®

Physical Sciences and Mathematics Commons

Open Access. Powered by Scholars. Published by Universities.®

Artificial Intelligence and Robotics

PDF

Air Force Institute of Technology

Genetic algorithms

Publication Year

Articles 1 - 2 of 2

Full-Text Articles in Physical Sciences and Mathematics

Exploitation Of Self Organization In Uav Swarms For Optimization In Combat Environments, Dustin J. Nowak Mar 2008

Exploitation Of Self Organization In Uav Swarms For Optimization In Combat Environments, Dustin J. Nowak

Theses and Dissertations

This investigation focuses primarily on the development of effective target engagement for unmanned aerial vehicle (UAV) swarms using autonomous self-organized cooperative control. This development required the design of a new abstract UAV swarm control model which flows from an abstract Markov structure, a Partially Observable Markov Decision Process. Self-organization features, bio-inspired attack concepts, evolutionary computation (multi-objective genetic algorithms, differential evolution), and feedback from environmental awareness are instantiated within this model. The associated decomposition technique focuses on the iterative deconstruction of the problem domain state and dynamically building-up of self organizational rules as related to the problem domain environment. Resulting emergent …


Discovery Learning In Autonomous Agents Using Genetic Algorithms, Edward O. Gordon Dec 1993

Discovery Learning In Autonomous Agents Using Genetic Algorithms, Edward O. Gordon

Theses and Dissertations

As the new Distributed Interactive Simulation (DIS) draft standard evolves into a useful document and distributed simulations begin to emerge that implement parts of the standard, there is renewed interest in available methods to effectively control autonomous aircraft agents in such a simulated environment. This investigation examines the use of a genetics-based classifier system for agent control. These are robust learning systems that use the adaptive search mechanisms of genetic algorithms to guide the learning system in forming new concepts (decision rules) about its environment. By allowing the rule base to evolve, it adapts agent behavior to environmental changes. Addressed …