Eduardo Alonso

发表

Artificial Neural Networks for Control of a Grid-Connected Rectifier/Inverter Under Disturbance, Dynamic and Power Converter Switching Conditions

Shuhui Li, Michael Fairbank, Cameron Johnson, 2014, IEEE Transactions on Neural Networks and Learning Systems.

Back to optimality: a formal framework to express the dynamics of learning optimal behavior

Michael Fairbank, Eduardo Alonso, Esther Mondragón, 2015, Adapt. Behav..

Quantized Census for Stereoscopic Image Matching

Eduardo Alonso, Gregory G. Slabaugh, Chris Child, 2014, 2014 2nd International Conference on 3D Vision.

Visual scene classification for image and video home content

Eduardo Alonso, Paulo Villegas, Eduard Bru, 2008, 2008 International Workshop on Content-Based Multimedia Indexing.

Training Recurrent Neural Networks With the Levenberg–Marquardt Algorithm for Optimal Control of a Grid-Connected Converter

Shuhui Li, Michael Fairbank, Eduardo Alonso, 2015, IEEE Transactions on Neural Networks and Learning Systems.

Machine Learning for Logic-Based Multi-agent Systems

Daniel Kudenko, Eduardo Alonso, D. Kudenko, 2000, FAABS.

Deep Multi-Agent Reinforcement Learning for Cost Efficient Distributed Load Frequency Control pdf

Eduardo Alonso, Dimitra Apostolopoulou, Sergio Rozada, 2020, IET Energy Systems Integration.

DeepFMRI: End-to-end deep learning for functional connectivity and classification of ADHD using fMRI

Eduardo Alonso, Atif Riaz, Muhammad Asad, 2020, Journal of Neuroscience Methods.

Approximating Optimal Control with Value Gradient Learning

Michael Fairbank, Eduardo Alonso, Danil V. Prokhorov, 2013 .

The divergence of reinforcement learning algorithms with value-iteration and function approximation

Michael Fairbank, Eduardo Alonso, Michael Fairbank, 2011, The 2012 International Joint Conference on Neural Networks (IJCNN).

Hand Pose Estimation Using Deep Stereovision and Markov-Chain Monte Carlo

Eduardo Alonso, Gregory G. Slabaugh, Chris Child, 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

A Rescorla-Wagner drift-diffusion model of conditioning and timing

Eduardo Alonso, Esther Mondragón, André Luzardo, 2017, bioRxiv.

An adaptive recurrent neural-network controller using a stabilization matrix and predictive inputs to solve a tracking problem under disturbances

Shuhui Li, Michael Fairbank, Eduardo Alonso, 2014, Neural Networks.

A Semantic and Pragmatic Framework for the Specification of Agent Communication Languages: Motivational Attitudes and Norms

Eduardo Alonso, Rodrigo Agerri, Eduardo Alonso, 2005, AOIS.

Coordination Efficiency in Rational Choice Theory, Norm and Rights Based Multi-agent Systems

Eduardo Alonso, Peter Kristoffersson, Eduardo Alonso, 2005, AOIS.

How individuals negotiate societies

Eduardo Alonso, 1998, Proceedings International Conference on Multi Agent Systems (Cat. No.98EX160).

A Rescorla-Wagner Drift-Diffusion Model of Conditioning and Timing

Eduardo Alonso, Esther Mondragón, André Luzardo, 2017 .

Towards a Personalised Health System

Eduardo Alonso, Peter Weller, Alberto Fernández Gil, 2014, HEALTHINF.

HandyDepth: Example-based stereoscopic hand depth estimation using Eigen Leaf Node Features

Eduardo Alonso, Gregory G. Slabaugh, Christopher Child, 2016, 2016 International Conference on Systems, Signals and Image Processing (IWSSIP).

Clipping in Neurocontrol by Adaptive Dynamic Programming

Michael Fairbank, Eduardo Alonso, Danil V. Prokhorov, 2014, IEEE Transactions on Neural Networks and Learning Systems.

Data-driven recovery of hand depth using CRRF on stereo images

Eduardo Alonso, Gregory G. Slabaugh, Chris Child, 2018, IET Comput. Vis..

A comparison of learning speed and ability to cope without exploration between DHP and TD(0)

Michael Fairbank, Eduardo Alonso, Michael Fairbank, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

A formal framework for the representation of negociation protocols

Eduardo Alonso, E. Alonso, 1997, Inteligencia Artif..

Efficient Calculation of the Gauss-Newton Approximation of the Hessian Matrix in Neural Networks

Michael Fairbank, Eduardo Alonso, Michael Fairbank, 2012, Neural Computation.

Phenotypic Integrated Framework for Classification of ADHD Using fMRI

Eduardo Alonso, Gregory G. Slabaugh, Atif Riaz, 2016, ICIAR.

Smart Security Audit: Reinforcement Learning with a Deep Neural Network Approximator

Eduardo Alonso, Vladimir Stankovic, Kevin Jones, 2020, 2020 International Conference on Cyber Situational Awareness, Data Analytics and Assessment (CyberSA).

Vector control of a grid-connected rectifier/inverter using an artificial neural network

Shuhui Li, Michael Fairbank, Eduardo Alonso, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

An Equivalence Between Adaptive Dynamic Programming With a Critic and Backpropagation Through Time

Michael Fairbank, Eduardo Alonso, Danil V. Prokhorov, 2013, IEEE Transactions on Neural Networks and Learning Systems.

The Local Optimality of Reinforcement Learning by Value Gradients, and its Relationship to Policy Gradient Learning pdf

Michael Fairbank, Eduardo Alonso, Michael Fairbank, 2011, ArXiv.

Emergent and Adaptive Systems of Systems

Michael Fairbank, Eduardo Alonso, Michael Fairbank, 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

Nested-loop neural network vector control of permanent magnet synchronous motors

Shuhui Li, Michael Fairbank, Eduardo Alonso, 2013, The 2013 International Joint Conference on Neural Networks (IJCNN).

Deep fMRI: AN end-to-end deep network for classification of fMRI data

Muhammad Asad, Eduardo Alonso, S. M. Masudur Rahman Al-Arif, 2018, 2018 IEEE 15th International Symposium on Biomedical Imaging (ISBI 2018).

Computational Models of Classical Conditioning - A Qualitative Evaluation and Comparison

Eduardo Alonso, Esther Mondragón, Pavandeep Sahota, 2014, ICAART.

Optimal Dispatch of Pumped Storage Hydro Cascade Under Uncertainty

Eduardo Alonso, Dimitra Apostolopoulou, Fatemeh Najibi, 2018, 2018 UKACC 12th International Conference on Control (CONTROL).

Simple and Fast Calculation of the Second-Order Gradients for Globalized Dual Heuristic Dynamic Programming in Neural Networks

Michael Fairbank, Eduardo Alonso, Danil V. Prokhorov, 2012, IEEE Transactions on Neural Networks and Learning Systems.

Towards Symbolic Reinforcement Learning with Common Sense pdf

Artur S. d'Avila Garcez, Eduardo Alonso, Aimore Resende Riquetti Dutra, 2018, ArXiv.

A reward-driven model of Darwinian fitness

Eduardo Alonso, Mark Broom, Jan Teichmann, 2015, 2015 7th International Joint Conference on Computational Intelligence (IJCCI).

FCNet: A Convolutional Neural Network for Calculating Functional Connectivity from Functional MRI

Eduardo Alonso, S. M. Masudur Rahman Al-Arif, Gregory G. Slabaugh, 2017, CNI@MICCAI.

Multiagent service architectures for bus fleet management

Sascha Ossowski, Eduardo Alonso, Alberto Fernández, 2004, Integr. Comput. Aided Eng..

Quantum Probability in Operant Conditioning - Behavioral Uncertainty in Reinforcement Learning

Eduardo Alonso, Esther Mondragón, 2014, ICAART.

Adaptive Agents and Multi-Agent Systems II: Adaptation and Multi-Agent Learning

Daniel Kudenko, Eduardo Alonso, Dimitar Kazakov, 2003, Adaptive Agents and Multi-Agent Systems.

A double error dynamic asymptote model of associative learning.

Eduardo Alonso, Esther Mondragón, Niklas H. B. Kokkola, 2019, Psychological review.

An extension of the Rescorla and Wagner Simulator for context conditioning

Eduardo Alonso, Esther Mondragón, Jonathan Gray, 2013, Comput. Methods Programs Biomed..

Associative Reinforcement Learning - A Proposal to Build Truly Adaptive Agents and Multi-agent Systems

Eduardo Alonso, Esther Mondragón, Eduardo Alonso, 2013, ICAART.

Normative Pragmatics for Agent Communication Languages

Eduardo Alonso, Rodrigo Agerri, Eduardo Alonso, 2005, ER.

Control of three-phase grid-connected microgrids using artificial neural networks

Shuhui Li, Michael Fairbank, Eduardo Alonso, 2015, 2015 7th International Joint Conference on Computational Intelligence (IJCCI).

Machine Learning Techniques for Adaptive Logic-Based Multi-Agent Systems

Daniel Kudenko, Eduardo Alonso, D. Kudenko, 1999 .

Neural-network based vector control of VSCHVDC transmission systems

Shuhui Li, Michael Fairbank, Eduardo Alonso, 2015, 2015 International Conference on Renewable Energy Research and Applications (ICRERA).

Semantics and Pragmatics for Agent Communication

Eduardo Alonso, Rodrigo Agerri, 2005, EPIA.

AI and Agents: State of the Art

Eduardo Alonso, E. Alonso, 2002, AI Mag..

Internally Driven Q-learning - Convergence and Generalization Results

Eduardo Alonso, Esther Mondragón, Niclas Kjäll-Ohlsson, 2012, ICAART.

An individualistic approach to social action in multi-agent systems

Eduardo Alonso, E. Alonso, 1999, J. Exp. Theor. Artif. Intell..

What Have Computational Models Ever Done for Us?: A Case Study in Classical Conditioning

Eduardo Alonso, Esther Mondragón, Eduardo Alonso, 2014, Int. J. Artif. Life Res..

Gaussian Process Regression for Probabilistic Short-term Solar Output Forecast pdf

Eduardo Alonso, Dimitra Apostolopoulou, Fatemeh Najibi, 2020, ArXiv.

Right-based Coordination for Environments with Changing Complexity - Results in Traffic Simulation

Eduardo Alonso, Peter Kristofersson-Izmajlow, 2013, ICAART.

Radiography Classification: A Comparison between Eleven Convolutional Neural Networks

Constantino Carlos Reyes-Aldasoro, Eduardo Alonso, Aram Ter-Sarkisov, 2020, 2020 Fourth International Conference on Multimedia Computing, Networking and Applications (MCNA).

Symmetries, groups, groupoids and systems of systems

Ali G. Hessami, Eduardo Alonso, Nicos Karcanias, 2013, 2013 IEEE International Systems Conference (SysCon).

Agency, Learning and Animal-Based Reinforcement Learning

Eduardo Alonso, Esther Mondragón, Eduardo Alonso, 2003, Agents and Computational Autonomy.

Groups and Societies: One and the Same Thing?

Eduardo Alonso, E. Alonso, 1998, IBERAMIA.

Rights for Multi-agent Systems

Eduardo Alonso, E. Alonso, 2002, Foundations and Applications of Multi-Agent Systems.

A Bayesian Argumentation Framework for Distributed Fault Diagnosis in Telecommunication Networks

Eduardo Alonso, Álvaro Carrera, Carlos A Iglesias, 2019, Sensors.

Fusion of fMRI and non-imaging data for ADHD classification

Eduardo Alonso, Gregory G. Slabaugh, Muhammad Asad, 2017, Comput. Medical Imaging Graph..

Performance evaluation of AMR simultaneous polling strategies in a PRIME PLC network

Eduardo Alonso, Javier Matanza, Sadot Alexandres, 2015, 2015 IEEE International Symposium on Power Line Communications and Its Applications (ISPLC).

Conditional Regressive Random Forest Stereo-Based Hand Depth Recovery

Eduardo Alonso, Gregory G. Slabaugh, Chris Child, 2017, 2017 IEEE International Conference on Computer Vision Workshops (ICCVW).

Modelling of integrated distillation plant

Sten Bay Jørgensen, Eduardo Alonso, 2002 .

Value-gradient learning

Michael Fairbank, Eduardo Alonso, Michael Fairbank, 2012, The 2012 International Joint Conference on Neural Networks (IJCNN).

Derechos, coordinacion y accion social en dominios multi-agentes

Eduardo Alonso, Eduardo Alonso, 1999, Inteligencia Artif..

The Workshops at the Twentieth National Conference on Artificial Intelligence

Gökhan Tür, Dilek Z. Hakkani-Tür, Mark S. Boddy, 2005, AI Mag..

Rights and Argumentation in Open Multi-Agent Systems

Eduardo Alonso, Eduardo Alonso, 2004, Artificial Intelligence Review.

Experimental Comparison of Rational Choice Theory, Norm and Rights Based Multi Agent Systems

Eduardo Alonso, Peter Kristoffersson, Eduardo Alonso, 2005, ER.

A Complete Serial Compound Temporal Difference Simulator for Compound stimuli, Configural cues and Context representation

Eduardo Alonso, Esther Mondragón, Jonathan Gray, 2012, Neuroinformatics.

Multi-agent learning

Eduardo Alonso, 2007, Autonomous Agents and Multi-Agent Systems.

Generating Magnetic Resonance Spectroscopy Imaging Data of Brain Tumours from Linear, Non-Linear and Deep Learning Models

Constantino Carlos Reyes-Aldasoro, Eduardo Alonso, Gregory G. Slabaugh, 2018, SASHIMI@MICCAI.

Machine Learning for Agents and Multi-Agent Systems

Daniel Kudenko, Eduardo Alonso, Dimitar Kazakov, 2008 .

A Java simulator of Rescorla and Wagner's prediction error model and configural cue extensions

Eduardo Alonso, Esther Mondragón, Alberto Fernández, 2012, Comput. Methods Programs Biomed..

Sistemas Logicos de Multiples Agentes: Arquitectura e Implementacion en Simuladores de Conflictos

Daniel Kudenko, Eduardo Alonso, 2001, Inteligencia Artif..

Adaptive Agents and Multi-Agent Systems

Daniel Kudenko, Eduardo Alonso, Dimitar Kazakov, 2003, Lecture Notes in Computer Science.

Associative Learning Should Go Deep

Eduardo Alonso, Esther Mondragón, Niklas H. B. Kokkola, 2017, Trends in Cognitive Sciences.

The application of temporal difference learning in optimal diet models.

Eduardo Alonso, Mark Broom, Eduardo Alonso, 2014, Journal of theoretical biology.