Evolving neural networks through augmenting topologies
Evolutionary Computation
Evolving Soccer Keepaway Players Through Task Decomposition
Machine Learning
Co-evolving recurrent neurons learn deep memory POMDPs
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Learning basic navigation for personal satellite assistant using neuroevolution
GECCO '05 Proceedings of the 7th annual conference on Genetic and evolutionary computation
Engineering industry controllers using neuroevolution
Artificial Intelligence for Engineering Design, Analysis and Manufacturing
Emergence of Cooperation: State of the Art
Artificial Life
Facilitating neural dynamics for delay compensation and prediction in evolutionary neural networks
Proceedings of the 8th annual conference on Genetic and evolutionary computation
Training Recurrent Networks by Evolino
Neural Computation
Proceedings of the 9th annual conference companion on Genetic and evolutionary computation
Specialization with NeuroEvolution in a collective behaviour task
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Proceedings of the 10th annual conference companion on Genetic and evolutionary computation
Neuro-evolution for a gathering and collective construction task
Proceedings of the 10th annual conference on Genetic and evolutionary computation
Accelerated Neural Evolution through Cooperatively Coevolved Synapses
The Journal of Machine Learning Research
Hierarchical Co-evolution of Cooperating Agents Acting in the Brain-Arena
Adaptive Behavior - Animals, Animats, Software Agents, Robots, Adaptive Systems
Proceedings of the 11th Annual Conference Companion on Genetic and Evolutionary Computation Conference: Late Breaking Papers
Anticipatory Behavior in Adaptive Learning Systems
Acquiring visibly intelligent behavior with example-guided neuroevolution
AAAI'07 Proceedings of the 22nd national conference on Artificial intelligence - Volume 1
Neuro-evolution approaches to collective behavior
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
Entropy and mutual information can improve fitness evaluation in coevolution of neural networks
CEC'09 Proceedings of the Eleventh conference on Congress on Evolutionary Computation
RL-Based Memory Controller for Scalable Autonomous Systems
ICONIP '09 Proceedings of the 16th International Conference on Neural Information Processing: Part II
Multi groups cooperation based symbiotic evolution for TSK-type neuro-fuzzy systems design
Expert Systems with Applications: An International Journal
Neuro-evolution methods for designing emergent specialization
ECAL'07 Proceedings of the 9th European conference on Advances in artificial life
Proceedings of the 12th annual conference companion on Genetic and evolutionary computation
EA'09 Proceedings of the 9th international conference on Artificial evolution
Proceedings of the 13th annual conference companion on Genetic and evolutionary computation
Efficient non-linear control through neuroevolution
ECML'06 Proceedings of the 17th European conference on Machine Learning
Comparative reproduction schemes for evolving gathering collectives
ECAL'05 Proceedings of the 8th European conference on Advances in Artificial Life
Expert Systems with Applications: An International Journal
Crossover-based local search in cooperative co-evolutionary feedforward neural networks
Applied Soft Computing
Proceedings of the 14th annual conference companion on Genetic and evolutionary computation
Parallel linear genetic programming for multi-class classification
Genetic Programming and Evolvable Machines
Evolving team behaviors with specialization
Genetic Programming and Evolvable Machines
Proceedings of the 15th annual conference on Genetic and evolutionary computation
Proceedings of the 15th annual conference companion on Genetic and evolutionary computation
Journal of Intelligent & Fuzzy Systems: Applications in Engineering and Technology
Hi-index | 0.00 |
Many complex control problems require sophisticated solutions that are not amenable to traditional controller design. Not only is it difficult to model real world systems, but often it is unclear what kind of behavior is required to solve the task. Reinforcement learning approaches have made progress in such problems, but have so far not scaled well. Neuroevolution, has improved upon conventional reinforcement learning, but has still not been successful in full-scale, non-linear control problems. This dissertation develops a methodology for solving real world control tasks consisting of three components: (1) an efficient neuroevolution algorithm that solves difficult non-linear control tasks by coevolving neurons, (2) an incremental evolution method to scale the algorithm to the most challenging tasks, and (3) a technique for making controllers robust so that they can transfer from simulation to the real world. The method is faster than other approaches on a set of difficult learning benchmarks, and is used in two full-scale control tasks demonstrating its applicability to real world problems.