A. Soltoggio

发表

Evolutionary Advantages of Neuromodulated Plasticity in Dynamic, Reward-based Scenarios

Dario Floreano, Claudio Mattiussi, Andrea Soltoggio, 2008, ALIFE.

Born to Learn: the Inspiration, Progress, and Future of Evolved Plastic Artificial Neural Networks

Sebastian Risi, Kenneth O. Stanley, Andrea Soltoggio, 2017, Neural Networks.

Evolutionary and Computational Advantages of Neuromodulated Plasticity

A. Soltoggio, Andrea Soltoggio, 2008 .

Context Meta-Reinforcement Learning via Neuromodulation

Praveen K. Pilly, Nicholas A. Ketz, A. Soltoggio, 2021, Neural Networks.

Convolutional neural networks for automated targeted analysis of gas chromatography-mass spectrometry data

A. Soltoggio, M. Sykora, D. Salman, 2019 .

Advances in Intelligent Systems and Computing

A. Soltoggio, C. Dawson, M. Pain, 2015 .

A Case Study of a Genetically Evolved Control System

A. Soltoggio, 2003 .

Wasserstein Task Embedding for Measuring Task Similarities

A. Soltoggio, S. Kolouri, Yikun Bai, 2022, ArXiv.

Lifelong Reinforcement Learning with Modulating Masks

Praveen K. Pilly, A. Soltoggio, S. Kolouri, 2022, ArXiv.

A Domain-Agnostic Approach for Characterization of Lifelong Learning Systems

Santhosh K. Ramakrishnan, Gautam K. Vallabha, Praveen K. Pilly, 2023, Neural Networks.

Neural Networks for Efficient Nonlinear Online Clustering

Andrea Soltoggio, Yanis Bahroun, Eugénie Hunsicker, 2017, ICONIP.

Building Efficient Deep Hebbian Networks for Image Classification Tasks

Andrea Soltoggio, Yanis Bahroun, Eugénie Hunsicker, 2017, ICANN.

Distributed Strategy Adaptation with a Prediction Function in Multi-Agent Task Allocation

Gerald Schaefer, Joanna Turner, Qinggang Meng, 2018, AAMAS.

VOCCluster: Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography - Mass Spectrometry Data.

Andrea Soltoggio, William H. Nailon, C. L. Paul Thomas, 2019, Analytical chemistry.

Evolution of neural symmetry and its coupled alignment to body plan morphology

Xin Yao, Bernhard Sendhoff, Ben Jones, 2011, GECCO '11.

Biological underpinnings for lifelong learning machines

Praveen K. Pilly, Nicholas A. Ketz, J. Clune, 2022, Nature Machine Intelligence.

How Rich Motor Skills Empower Robots at Last: Insights and Progress of the AMARSi Project

Jochen J. Steil, Andrea Soltoggio, J. Steil, 2012, KI - Künstliche Intelligenz.

POET: An Evo-Devo Method to Optimize the Weights of Large Artificial Neural Networks

Andrea Soltoggio, Alessandro Fontana, Borys Wróbel, 2014, ALIFE.

Real-time Hebbian Learning from Autoencoder Features for Control Tasks

Kenneth O. Stanley, Andrea Soltoggio, Justin K. Pugh, 2018, ALIFE.

Rare Neural Correlations Implement Robotic Conditioning with Delayed Rewards and Disturbances

Jochen J. Steil, René Felix Reinhart, Andrea Soltoggio, 2013, Front. Neurorobot..

Novelty of behaviour as a basis for the neuro-evolution of operant reward learning

Ben Jones, Andrea Soltoggio, A. Soltoggio, 2009, GECCO.

Detecting Changes and Avoiding Catastrophic Forgetting in Dynamic Partially Observable Environments

Soheil Kolouri, Praveen K. Pilly, Pawel Ladosz, 2020, Frontiers in Neurorobotics.

A Multi-Scale Mapping Approach Based on a Deep Learning CNN Model for Reconstructing High-Resolution Urban DEMs pdf

Yang Hu, Andrea Soltoggio, Xilin Xia, 2019, Water.

From modulated Hebbian plasticity to simple behavior learning through noise and weight saturation

Kenneth O. Stanley, Andrea Soltoggio, A. Soltoggio, 2012, Neural Networks.

GP and GA in the design of a constrained control system with disturbance rejection

A. Soltoggio, A. Soltoggio, Andrea Soltoggio, 2004, Proceedings of the 2004 IEEE International Symposium on Intelligent Control, 2004..

A Comparison of Genetic Programming and Genetic Algorithms in the Design of a Robust, Saturated Control System

Andrea Soltoggio, A. Soltoggio, Andrea Soltoggio, 2004, GECCO.

Lifelong Reinforcement Learning with Modulating Masks

Praveen K. Pilly, A. Soltoggio, S. Kolouri, 2022, ArXiv.

The configurable tree graph (CT-graph): measurable problems in partially observable and distal reward environments for lifelong reinforcement learning

Praveen K. Pilly, A. Soltoggio, S. Kolouri, 2023, ArXiv.

Sliced Cramer Synaptic Consolidation for Preserving Deeply Learned Representations

Soheil Kolouri, Andrea Soltoggio, Praveen K. Pilly, 2020, ICLR.

Deep Reinforcement Learning With Modulated Hebbian Plus Q-Network Architecture

Jeffrey L. Krichmar, Soheil Kolouri, Andrea Soltoggio, 2019, IEEE Transactions on Neural Networks and Learning Systems.

Evolving inborn knowledge for fast adaptation in dynamic POMDP problems

Wen-Hua Chen, Praveen K. Pilly, Pawel Ladosz, 2020, GECCO.

Solving the Distal Reward Problem with Rare Correlations

Jochen J. Steil, Andrea Soltoggio, J. Steil, 2013, Neural Computation.

A Fully Convolutional Two-Stream Fusion Network for Interactive Image Segmentation

Yang Hu, Steve Carter, Andrea Soltoggio, 2018, Neural Networks.

Virtual Reality Study of Human Adaptability in Industrial Human-Robot Collaboration

Yee Mey Goh, Peter Kinnell, Andrea Soltoggio, 2020, 2020 IEEE International Conference on Human-Machine Systems (ICHMS).

Understanding Human Behaviour in Industrial Human-Robot Interaction by Means of Virtual Reality

Yee Mey Goh, Andrea Soltoggio, Peter Kinnell, 2019, HTTF.

Distributed Task Rescheduling With Time Constraints for the Optimization of Total Task Allocations in a Multirobot System

Gerald Schaefer, Joanna Turner, Qinggang Meng, 2018, IEEE Transactions on Cybernetics.

Short-term plasticity as cause–effect hypothesis testing in distal reward learning

Andrea Soltoggio, A. Soltoggio, Andrea Soltoggio, 2014, Biological Cybernetics.

Untargeted Metabolomics Feature Clustering Approach for Clinical Breath Gas Chromatography-Mass Spectrometry Data

Andrea Soltoggio, William H. Nailon, Michael Eddleston, 2019 .

Sharing Lifelong Reinforcement Learning Knowledge via Modulating Masks

Soheil Kolouri, A. Soltoggio, S. Kolouri, 2023, ArXiv.

Robot apology as a post-accident trust-recovery control strategy in industrial human-robot interaction

Yee Mey Goh, Andrea Soltoggio, Peter Kinnell, 2021 .

Short-term plasticity as cause–effect hypothesis testing in distal reward learning

A. Soltoggio, 2014, Biological Cybernetics.

Evolving neuromodulatory topologies for reinforcement learning-like problems

Dario Floreano, Claudio Mattiussi, Andrea Soltoggio, 2007, 2007 IEEE Congress on Evolutionary Computation.

Lifelong Reinforcement Learning with Modulating Masks

Praveen K. Pilly, A. Soltoggio, S. Kolouri, 2022, ArXiv.