Andrea Soltoggio
Cited by
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Evolutionary advantages of neuromodulated plasticity in dynamic, reward-based scenarios
A Soltoggio, JA Bullinaria, C Mattiussi, P Dürr, D Floreano
Proceedings of the 11th international conference on artificial life (Alife …, 2008
Born to learn: the inspiration, progress, and future of evolved plastic artificial neural networks
A Soltoggio, KO Stanley, S Risi
Neural Networks 108, 48-67, 2018
Evolving neuromodulatory topologies for reinforcement learning-like problems
A Soltoggio, P Durr, C Mattiussi, D Floreano
2007 IEEE Congress on evolutionary computation, 2471-2478, 2007
A fully convolutional two-stream fusion network for interactive image segmentation
Y Hu, A Soltoggio, R Lock, S Carter
Neural Networks 109, 31-42, 2019
Distributed task rescheduling with time constraints for the optimization of total task allocations in a multirobot system
J Turner, Q Meng, G Schaefer, A Whitbrook, A Soltoggio
IEEE transactions on cybernetics 48 (9), 2583-2597, 2017
Evolvability of neuromodulated learning for robots
P Dürr, C Mattiussi, A Soltoggio, D Floreano
2008 ECSIS Symposium on Learning and Adaptive Behaviors for Robotic Systems …, 2008
From modulated Hebbian plasticity to simple behavior learning through noise and weight saturation
A Soltoggio, KO Stanley
Neural Networks 34, 28–41, 2012
Solving the distal reward problem with rare correlations
A Soltoggio, JJ Steil
Neural computation 25 (4), 940-978, 2013
Novelty of behaviour as a basis for the neuro-evolution of operant reward learning
A Soltoggio, B Jones
Proceedings of the 11th Annual conference on Genetic and evolutionary …, 2009
Online representation learning with single and multi-layer Hebbian networks for image classification
Y Bahroun, A Soltoggio
International Conference on Artificial Neural Networks, 354-363, 2017
Short-term plasticity as cause-effect hypothesis testing in distal reward learning
A Soltoggio
Biological Cybernetics, 1-20, 2014
VOCCluster: Untargeted metabolomics feature clustering approach for clinical breath gas chromatography/mass spectrometry data
Y Alkhalifah, I Phillips, A Soltoggio, K Darnley, WH Nailon, D McLaren, ...
Analytical chemistry 92 (4), 2937-2945, 2019
Distributed strategy adaptation with a prediction function in multi-agent task allocation
J Turner, Q Meng, G Schaefer, A Soltoggio
Loughborough University, 2018
Rare neural correlations implement robotic conditioning with delayed rewards and disturbances
A Soltoggio, A Lemme, F Reinhart, JJ Steil
Frontiers in Neurorobotics 7, 6, 2013
Convolutional neural networks for automated targeted analysis of raw gas chromatography-mass spectrometry data
A Skarysz, Y Alkhalifah, K Darnley, M Eddleston, Y Hu, DB McLaren, ...
2018 International Joint Conference on Neural Networks (IJCNN), 1-8, 2018
Neural plasticity and minimal topologies for reward-based learning
A Soltoggio
2008 Eighth International Conference on Hybrid Intelligent Systems, 637-642, 2008
Neuromodulation increases decision speed in dynamic environments
A Soltoggio
Proceedings of the 8th International Conference on Epigenetic Robotics …, 2008
A comparison of genetic programming and genetic algorithms in the design of a robust, saturated control system
A Soltoggio
Genetic and Evolutionary Computation Conference, 174-185, 2004
An enhanced GA to improve the search process reliability in tuning of control systems
A Soltoggio
Proceedings of the 7th annual conference on Genetic and evolutionary …, 2005
Evolutionary Algorithms in the Design and Tuning of a Control System
A Soltoggio
Department of Computer and Information Science Norwegian University of …, 2004
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