Evolutionary computation: toward a new philosophy of machine intelligence
Evolutionary computation: toward a new philosophy of machine intelligence
Properties of fitness functions and search landscapes
Theoretical aspects of evolutionary computing
Information, Randomness and Incompleteness
Information, Randomness and Incompleteness
The Advantages of Landscape Neutrality in Digital Circuit Evolution
ICES '00 Proceedings of the Third International Conference on Evolvable Systems: From Biology to Hardware
An information-theoretic landscape analysis of neuro-controlled embodied organisms
Neural Computing and Applications
Information Characteristics and the Structure of Landscapes
Evolutionary Computation
Evolving agents for network centric warfare
GECCO '05 Proceedings of the 7th annual workshop on Genetic and evolutionary computation
A Comprehensive Overview of the Applications of Artificial Life
Artificial Life
An Evaluation Framework for MAS Modeling Languages Based on Metamodel Metrics
Agent-Oriented Software Engineering IX
LSMS/ICSEE'10 Proceedings of the 2010 international conference on Life system modeling and and intelligent computing, and 2010 international conference on Intelligent computing for sustainable energy and environment: Part I
Land combat scenario planning: a multiobjective approach
SEAL'06 Proceedings of the 6th international conference on Simulated Evolution And Learning
WISDOM-II: a network centric model for warfare
KES'05 Proceedings of the 9th international conference on Knowledge-Based Intelligent Information and Engineering Systems - Volume Part III
Evolvable simulations applied to automated red teaming: a preliminary study
Proceedings of the Winter Simulation Conference
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Traditionally optimization of defence operations are based on the findings of human-based war gaming However, this approach is extremely expensive and does not enable analysts to explore the problem space properly Recent research shows that both computer simulations of multi-agent systems and evolutionary computation are valuable tools for optimizing defence operations A potential maneuver strategy is generated by the evolutionary method then gets evaluated by calling the multi–agent simulation module to simulate the system behavior The optimization problem in this context is known as a black box optimization problem, where the function that is being optimized is hidden and the only information we have access to is through the value(s) returned from the simulation for a given input set However, to design efficient search algorithms, it is necessary to understand the properties of this search space; thus unfolding some characteristics of the black box Without doing so, one cannot estimate how good the results are, neither can we design competent algorithms that are able to deal with the problem properly In this paper, we provide a first attempt at understanding the characteristics and properties of the search space of complex adaptive combat systems.