C. Anderson

发表

Neuronlike adaptive elements that can solve difficult learning control problems

Richard S. Sutton, Andrew G. Barto, Charles W. Anderson, 1983, IEEE Transactions on Systems, Man, and Cybernetics.

Synthesis of reinforcement learning, neural networks and PI control applied to a simulated heating coil

Douglas C. Hittle, Charles W. Anderson, Alon D. Katz, 1997, Artificial Intelligence in Engineering.

Multigrid Q-learning

C. Anderson, S. Crawford-Hines, 1994 .

Strategy Learning with Multilayer Connectionist Representations

Charles W. Anderson, C. Anderson, 1987 .

Learning and problem-solving with multilayer connectionist systems (adaptive, strategy learning, neural networks, reinforcement learning)

Charles W. Anderson, C. Anderson, 1986 .

Synthesis of nonlinear control surfaces by a layered associative search network

R. Sutton, A. Barto, C. Anderson, 2004, Biological Cybernetics.

Genetic Reinforcement Learning for Neurocontrol Problems

L. D. Whitley, C. Anderson, R. Das, 2004, Machine Learning.

Learning to Control an Inverted Pendulum with Connectionist Networks

Charles W. Anderson, C. Anderson, 1988, 1988 American Control Conference.

Connectionist Learning Control at GTE Laboratories

Richard S. Sutton, Oliver G. Selfridge, Charles W. Anderson, 1990, Other Conferences.

Strategy Learning with Multilayer Connectionist Representations 1

C. Anderson, 1987 .

Learning to control an inverted pendulum using neural networks

C.W. Anderson, C. Anderson, Charles Anderson, 1989, IEEE Control Systems Magazine.

Q-Learning with Hidden-Unit Restarting

Charles W. Anderson, C. Anderson, 1992, NIPS.

Approximating a Policy Can be Easier Than Approximating a Value Function

Charles W. Anderson, C. Anderson, 2000 .

Looking Back on the Actor–Critic Architecture

Richard S. Sutton, Andrew G. Barto, Charles W. Anderson, 2021, IEEE Transactions on Systems, Man, and Cybernetics: Systems.

Efficient indexing for object recognition using large networks

Charles W. Anderson, J. R. Beveridge, M. R. Stevens, 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

Classification of EEG Signals from Four Subjects During Five Mental Tasks

Charles W. Anderson, C. Anderson, 2007 .

Multivariate Autoregressive Models for Classification of Spontaneous Electroencephalogram During Mental Tasks1

E. A. Stolz, C. Anderson, 1998 .

EEG signal compression with ADPCM subband coding

Charles W. Anderson, Z. Sijercic, G. C. Agarwal, 1996, Proceedings of the 39th Midwest Symposium on Circuits and Systems.

Feature Selection and Blind Source Separation in an EEG-Based Brain-Computer Interface

James N. Knight, Charles W. Anderson, David A. Peterson, 2005, EURASIP J. Adv. Signal Process..

Failure‐resilient real‐time processing of health streams

Shrideep Pallickara, Charles W. Anderson, Kathleen Ericson, 2015, Concurr. Comput. Pract. Exp..

EEG character identification using stimulus sequences designed to maximize mimimal hamming distance

Charles W. Anderson, Takamasa Shimada, Tadanori Fukami, 2012, 2012 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Restricted gradient-descent algorithm for value-function approximation in reinforcement learning

André da Motta Salles Barreto, Charles W. Anderson, André Barreto, 2008, Artif. Intell..

EEG-based Cognitive Task Classification with ICA and Neural Networks

Charles W. Anderson, David A. Peterson, C. Anderson, 1999, IWANN.

Covariance Regularization for Supervised Learning in High Dimensions

Michael Kirby, Charles W. Anderson, Daniel L. Elliott, 2010 .

EEG Subspace Representations and Feature Selection for Brain-Computer Interfaces

Charles W. Anderson, Michael J. Kirby, C. Anderson, 2003, 2003 Conference on Computer Vision and Pattern Recognition Workshop.

Identifying Mental Tasks from Spontaneous EEG: Signal Representation and Spatial Analysis

Charles W. Anderson, C. Anderson, 1999, IWANN.

Proceedings of the 1st International Workshop on Robot Learning and Planning (RLP 2016) pdf

Nancy M. Amato, Gregory S. Chirikjian, Geoffrey A. Hollinger, 2016, ArXiv.

EEG as a means of communication: preliminary experiments in EEG analysis using neural networks

Charles W. Anderson, E. A. Stolz, Saikumar V. Devulapalli, 1994, ASSETS.

Determining Mental State from EEG Signals Using Parallel Implementations of Neural Networks

Charles W. Anderson, E. A. Stolz, Saikumar V. Devulapalli, 1995, Sci. Program..

Classification of EEG during imagined mental tasks by forecasting with Elman Recurrent Neural Networks

Charles W. Anderson, Elliott M. Forney, C. Anderson, 2011, The 2011 International Joint Conference on Neural Networks.

Translating Thoughts Into Actions by Finding Patterns in Brainwaves

C. Anderson, Jeshua Bratman, 2008 .

Faster reinforcement learning after pretraining deep networks to predict state dynamics

Minwoo Lee, Charles W. Anderson, Daniel L. Elliott, 2015, 2015 International Joint Conference on Neural Networks (IJCNN).

An Experimental System for Advanced Heating, Ventilating and Air Conditioning (HVAC) Control

Douglas C. Hittle, Charles W. Anderson, Jilin Tu, 2007 .

IEEE TRANSACTIONS ON NEURAL NETWORKS AND LEARNING SYSTEMS Publication Information

Michael J. Watts, Haibo He, Giorgio Battistelli, 2020, IEEE Transactions on Neural Networks and Learning Systems.

EEG signal classification with different signal representations

Charles W. Anderson, E. A. Stolz, S. V. Devulapalli, 1995, Proceedings of 1995 IEEE Workshop on Neural Networks for Signal Processing.

Analyzing Electroencephalograms Using Cloud Computing Techniques

Shrideep Pallickara, Charles W. Anderson, Kathleen Ericson, 2010, 2010 IEEE Second International Conference on Cloud Computing Technology and Science.

AI Assisted Annotator using Reinforcement Learning pdf

Charles W. Anderson, V. Ratna Saripalli, Gopal Avinash, 2019, SN Comput. Sci..

Dissociating the contributions of independent corticostriatal systems to visual categorization learning through the use of reinforcement learning modeling and Granger causality modeling

Erik J. Peterson, Charles W. Anderson, Carol A. Seger, 2010, NeuroImage.

Convergent reinforcement learning control with neural networks and continuous action search

Minwoo Lee, Charles W. Anderson, C. Anderson, 2014, 2014 IEEE Symposium on Adaptive Dynamic Programming and Reinforcement Learning (ADPRL).

Discriminating mental tasks using EEG represented by AR models

Charles W. Anderson, S. Shamsunder, E. A. Stolz, 1995, Proceedings of 17th International Conference of the Engineering in Medicine and Biology Society.

Cooperativity in Networks of Pattern Recognizing Stochastic Learning Automata

P. Anandan, Andrew G. Barto, Charles W. Anderson, 1986 .

Traac Light Control Using Sarsa with Three State Representations

Thomas L. Thorpe, C. Anderson, T. Thorpe, 1996 .

Genetic Reinforcement Learning for Neurocontrol Problems

L. Darrell Whitley, L. D. Whitley, C. Anderson, 2004, Machine Learning.

Comparison of CMACs and radial basis functions for local function approximators in reinforcement learning

Charles W. Anderson, R. M. Kretchmar, C. Anderson, 1997, Proceedings of International Conference on Neural Networks (ICNN'97).

Genetic reinforcement learning for neural networks

Rajarshi Das, Charles W. Anderson, Darrell Whitley, 1991, IJCNN-91-Seattle International Joint Conference on Neural Networks.

Multivariate autoregressive models for classification of spontaneous electroencephalographic signals during mental tasks

C.W. Anderson, S. Shamsunder, E. A. Stolz, 1998, IEEE Transactions on Biomedical Engineering.

Effects of Variations in Neural Network Topology and Output Averaging on the Discrimination of Mental Tasks from Spontaneous Electroencephalogram

Charles W. Anderson, C. Anderson, 1997 .

Workshops of the Fifth International Brain-Computer

C. Anderson, A. Brouwer, A. Batista, 2014 .

Stable reinforcement learning with recurrent neural networks

C. Anderson, J. Knight, 2011 .

A Comparison of EEG Systems for Use in P 300 Spellers by Users With Motor Impairments in Real-World Environments

C. Anderson, E. Forney, W. Gavin, 2013 .

A Stimulus-Free Brain-Computer Interface Using Mental Tasks and Echo State Networks

C. Anderson, E. Forney, W. Gavin, 2013 .

A Multigrid Form of Value IterationApplied to a Markov Decision

Robert B. Heckendorn, C. Anderson, 1998 .

A Multigrid Form of Value Iteration Applied to a Markov Decision Problem

Robert B. Heckendorn, C. Anderson, 1998 .

Geometric subspace methods and time-delay embedding for EEG artifact removal and classification

C.W. Anderson, J.N. Knight, T. O'Connor, 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Reinforcement Learning, Neural Networks and PI Control Applied to a Heating Coil

Douglas C. Hittle, Charles W. Anderson, C. Anderson, 1996 .

Cluster Analysis of Neural Network Weights for Discrimination of Eeg Signals

C. Anderson, 2007 .

Echo State Networks for Modeling and Classification of EEG Signals in Mental-Task Brain-Computer Interfaces

C. Anderson, E. Forney, P. Davies, 2015 .

The Wisdom of the Crowd: Reliable Deep Reinforcement Learning Through Ensembles of Q-Functions

Charles W. Anderson, Daniel L. Elliott, C. Anderson, 2018, IEEE Transactions on Neural Networks and Learning Systems.

Dynamic Control of Soft Robots Using Reinforcement Learning

Jianguo Zhao, Charles W. Anderson, Ben Pawlowski, 2019, Volume 2: Modeling and Control of Engine and Aftertreatment Systems; Modeling and Control of IC Engines and Aftertreatment Systems; Modeling and Validation; Motion Planning and Tracking Control; Multi-Agent and Networked Systems; Renewable and Smart Energ.

Auditory priming improves neural synchronization in auditory-motor entrainment

C. Anderson, M. Thaut, P. Davies, 2018, Neuropsychologia.

Neural network approach to stream-aquifer modeling for improved river basin management

Charles W. Anderson, John W. Labadie, Timothy K. Gates, 2010 .

Linear and nonlinear methods for brain-computer interfaces

K.-R. Muller, C.W. Anderson, G.E. Birch, 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Workshops of the Sixth International Brain–Computer Interface Meeting: brain–computer interfaces past, present, and future

Ricardo Chavarriaga, Anton Nijholt, Reinhold Scherer, 2017, Brain computer interfaces.

Comparison of linear, nonlinear, and feature selection methods for EEG signal classification

C.W. Anderson, D. Garrett, D.A. Peterson, 2003, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Robust Reinforcement Learning Control Using Integral Quadratic Constraints for Recurrent Neural Networks

Douglas C. Hittle, James N. Knight, Charles W. Anderson, 2007, IEEE Transactions on Neural Networks.

Workshops of the Fifth International Brain-Computer Interface Meeting: Defining the Future.

Ricardo Chavarriaga, Clemens Brunner, Fabien Lotte, 2014, Brain computer interfaces.

Behavioral Cloning of Student Pilots with Modular Neural Networks

Bruce A. Draper, Charles W. Anderson, David A. Peterson, 2000, ICML.

EEG P300 wave detection using Emotiv EPOC+: Effects of matrix size, flash duration, and colors

Saleh Alzahrani, Charles W. Anderson, C. Anderson, 2017 .

Workshops of the Seventh International Brain-Computer Interface Meeting: Not Getting Lost in Translation.

Ricardo Chavarriaga, Anton Nijholt, Matthias Hohmann, 2019, Brain computer interfaces.

Gradient boosting in crowd ensembles for Q-learning using weight sharing

K. C. Santosh, Daniel L. Elliott, Charles Anderson, 2020, Int. J. Mach. Learn. Cybern..

Critical issues in state-of-the-art brain–computer interface signal processing

Moritz Grosse-Wentrup, Damien Coyle, Dean J Krusienski, 2011, Journal of neural engineering.

Robust Reinforcement Learning with Relevance Vector Machines

Charles W. Anderson, Minwoo Lee, C. Anderson, 2016 .

BCI meeting 2005-workshop on BCI signal processing: feature extraction and translation

K.-R. Muller, C.W. Anderson, A. Schlogl, 2006, IEEE Transactions on Neural Systems and Rehabilitation Engineering.

Classifying environmental features from local observations of emergent swarm behavior

Anthony A. Maciejewski, Megan Emmons, A. A. Maciejewski, 2020, IEEE/CAA Journal of Automatica Sinica.

Reinforcement Learning with Modular Neural Networks for Control

Charles W. Anderson, Z. Hong, C. Anderson, 1994 .

Can a reinforcement learning agent practice before it starts learning?

Minwoo Lee, Charles W. Anderson, C. Anderson, 2017, 2017 International Joint Conference on Neural Networks (IJCNN).

Reliable identification of mental tasks using time-embedded EEG and sequential evidence accumulation

Annamalai Natarajan, Charles Anderson, Elliott Forney, 2011, Journal of neural engineering.

Nonlinear dimensionality reduction of electroencephalogram (EEG) for Brain Computer interfaces

Mohammad Nayeem Teli, Charles Anderson, C. Anderson, 2009, 2009 Annual International Conference of the IEEE Engineering in Medicine and Biology Society.

Echo State Networks for Modeling and Classification of EEG Signals in Mental-Task Brain-Computer Interfaces

C. Anderson, E. Forney, P. Davies, 2015 .