Incremental evolution of complex general behavior
Adaptive Behavior - Special issue on environment structure and behavior
Evolutionary neurocontrollers for autonomous mobile robots
Neural Networks - Special issue on neural control and robotics: biology and technology
Embedded neural networks: exploiting constraints
Neural Networks - Special issue on neural control and robotics: biology and technology
Sharing the cost of multicast transmissions
Journal of Computer and System Sciences - Special issue on Internet algorithms
Active vision and feature selection in evolutionary behavioral systems
ICSAB Proceedings of the seventh international conference on simulation of adaptive behavior on From animals to animats
Localization of function via lesion analysis
Neural Computation
High-dimensional analysis of evolutionary autonomous agents
Artificial Life
ADUS: Indirect Generation of User Interfaces on Wireless Devices
DEXA '04 Proceedings of the Database and Expert Systems Applications, 15th International Workshop
Emergence of Memory-Driven Command Neurons in Evolved Artificial Agents
Neural Computation
Competitive coevolution through evolutionary complexification
Journal of Artificial Intelligence Research
Evolution of homing navigation in a real mobile robot
IEEE Transactions on Systems, Man, and Cybernetics, Part B: Cybernetics
The animat contribution to cognitive systems research
Cognitive Systems Research
IEEE Transactions on Neural Networks
Neurocontroller Analysis via Evolutionary Network Minimization
Artificial Life
Feature Selection via Coalitional Game Theory
Neural Computation
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
A game theoretic approach for feature clustering and its application to feature selection
PAKDD'11 Proceedings of the 15th Pacific-Asia conference on Advances in knowledge discovery and data mining - Volume Part I
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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One of the major challenges in the field of neurally driven evolved autonomous agents is deciphering the neural mechanisms underlying their behavior. Aiming at this goal, we have developed the multi-perturbation Shapley value analysis (MSA)—the first axiomatic and rigorous method for deducing causal function localization from multiple-perturbation data, substantially improving on earlier approaches. Based on fundamental concepts from game theory, the MSA provides a formal way of defining and quantifying the contributions of network elements, as well as the functional interactions between them. The previously presented versions of the MSA require full knowledge (or at least an approximation) of the network's performance under all possible multiple perturbations, limiting their applicability to systems with a small number of elements. This article focuses on presenting new scalable MSA variants, allowing for the analysis of large complex networks in an efficient manner, including large-scale neurocontrollers. The successful operation of the MSA along with the new variants is demonstrated in the analysis of several neurocontrollers solving a food foraging task, consisting of up to 100 neural elements.