Introduction to Probability and Statistics: Principles and Applications for Engineering and the Computing Sciences
Self-Organization in Biological Systems
Self-Organization in Biological Systems
The Complexity of Decentralized Control of Markov Decision Processes
Mathematics of Operations Research
Artificial Intelligence: A Modern Approach
Artificial Intelligence: A Modern Approach
Self-organization in multi-agent systems
The Knowledge Engineering Review
Towards autonomous mobile agents with emergent migration behaviour
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
AAMAS '06 Proceedings of the fifth international joint conference on Autonomous agents and multiagent systems
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
Evolutionary Algorithms for Solving Multi-Objective Problems (Genetic and Evolutionary Computation)
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Effective and efficient Cyber-security management is of central importance in military environments. Many contemporary military communication control structures are based on static, hierarchical designs, which generally lack scalability and flexibility due centralization. Thus, we propose a self organized entangled hierarchial architecture of multiple agents that decentralizes network security control and communication. In particular, we focus on the military CyberCraft container structure. The self organized multi-agent swarms are evolved based on partially observable Markov decision process formal models. Desired swarm behaviors are formalized to interact with these models. The "optimal" policy (agent rules and parameters) for a given behavior is evolved using a multi-objective evolutionary algorithm. Swarm effectiveness is compared in numerous military network security scenarios using statistical testing techniques and visualization.