Evolving neural networks through augmenting topologies
Evolutionary Computation
Adding Continuous Components to L-Systems
L Systems, Most of the papers were presented at a conference in Aarhus, Denmark
Networks analysis, complexity, and brain function
Complexity - Special issue: Selection, tinkering, and emergence in complex networks
A Taxonomy for artificial embryogeny
Artificial Life
Evolving modular genetic regulatory networks
CEC '02 Proceedings of the Evolutionary Computation on 2002. CEC '02. Proceedings of the 2002 Congress - Volume 02
Compositional pattern producing networks: A novel abstraction of development
Genetic Programming and Evolvable Machines
Competitive coevolution through evolutionary complexification
Journal of Artificial Intelligence Research
Real-time neuroevolution in the NERO video game
IEEE Transactions on Evolutionary 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
Generative and developmental systems
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Generative encoding for multiagent learning
Proceedings of the 10th annual conference on Genetic and evolutionary computation
How generative encodings fare on less regular problems
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Tree-Based Indirect Encodings for Evolutionary Development of Neural Networks
ICANN '08 Proceedings of the 18th international conference on Artificial Neural Networks, Part II
How a Generative Encoding Fares as Problem-Regularity Decreases
Proceedings of the 10th international conference on Parallel Problem Solving from Nature: PPSN X
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Generative and developmental systems
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
A case study on the critical role of geometric regularity in machine learning
AAAI'08 Proceedings of the 23rd national conference on Artificial intelligence - Volume 2
HyperNEAT controlled robots learn how to drive on roads in simulated environment
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Combining Multiple Inputs in HyperNEAT Mobile Agent Controller
ICANN '09 Proceedings of the 19th International Conference on Artificial Neural Networks: Part II
Unsupervised learning of echo state networks: a case study in artificial embryogeny
EA'07 Proceedings of the Evolution artificielle, 8th international conference on Artificial evolution
NEAT in HyperNEAT substituted with genetic programming
ICANNGA'09 Proceedings of the 9th international conference on Adaptive and natural computing algorithms
Evolving the placement and density of neurons in the hyperneat substrate
Proceedings of the 12th annual conference on Genetic and evolutionary computation
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Generative and developmental systems
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
Evolving a single scalable controller for an octopus arm with a variable number of segments
PPSN'10 Proceedings of the 11th international conference on Parallel problem solving from nature: Part II
Evolving neural networks for geometric game-tree pruning
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Constraining connectivity to encourage modularity in HyperNEAT
Proceedings of the 13th annual conference on Genetic and evolutionary computation
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Distance measures for HyperGP with fitness sharing
Proceedings of the 14th annual conference on Genetic and evolutionary computation
Generative and developmental systems
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
A study on scalable representations for evolutionary optimization of ground structures
Evolutionary Computation
Evolving large-scale neural networks for vision-based reinforcement learning
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Generative and developmental systems
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
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A significant problem for evolving artificial neural networks is that the physical arrangement of sensors and effectors is invisible to the evolutionary algorithm. For example, in this paper, directional sensors and effectors are placed around the circumference of a robot in analogous arrangements. This configuration ensures that there is a useful geometric correspondence between sensors and effectors. However, if sensors are mapped to a single input layer and the effectors to a single output layer (as is typical), evolution has no means to exploit this fortuitous arrangement. To address this problem, this paper presents a novel generative encoding called connective Compositional Pattern Producing Networks (connective CPPNs) that can effectively detect and capitalize on geometric relationships among sensors and effectors. The key insight is that sensors and effectors with consistent geometric relationships can be exploited by a repeating motif in the neural architecture. Thus, by employing an encoding that can discover such motifs as a function of network geometry, it becomes possible to exploit it. In this paper, a method for evolving connective CPPNs called Hypercube-based Neuroevolution of Augmenting Topologies (HyperNEAT) discovers sensible repeating motifs that take advantage of two different placement schemes, demonstrating the utility of such an approach.