Neuronlike adaptive elements that can solve difficult learning control problems. - Andrew G. Barto; Richard S. Sutton; Charles W. Anderson (IEEE Trans. Syst. Man Cybern., 1983)

Tower of Hanoi with Connectionist Networks: Learning New Features. - Charles W. Anderson (ML, 1989)

Q-Learning with Hidden-Unit Restarting. - Charles W. Anderson (NIPS, 1992)

EEG as a means of communication: preliminary experiments in EEG analysis using neural networks. - Charles W. Anderson; Saikumar V. Devulapalli; Erik A. Stolz (ASSETS, 1994)

On the Use of Neural Networks to Guide Software Testing Activities. - Charles Anderson 001; Anneliese von Mayrhauser; Richard T. Mraz (ITC, 1995)

Determining Mental State from EEG Signals Using Parallel Implementations of Neural Networks. - Charles W. Anderson; Saikumar V. Devulapalli; Erik A. Stolz (Sci. Program., 1995)

Assessing Neural Networks as Guides for Testing Activities. - Charles Anderson 001; Anneliese von Mayrhauser; Tom Chen 001 (IEEE METRICS, 1996)

Comparison of CMACs and radial basis functions for local function approximators in reinforcement learning. - R. Matthew Kretchmar; Charles W. Anderson (ICNN, 1997)

Efficient indexing for object recognition using large networks. - Mark R. Stevens; Charles W. Anderson; J. Ross Beveridge (ICNN, 1997)

Synthesis of reinforcement learning, neural networks and PI control applied to a simulated heating coil. - Charles W. Anderson; Douglas C. Hittle; Alon D. Katz; R. Matthew Kretchmar (Artif. Intell. Eng., 1997)

Fast Antirandom (FAR) Test Generation. - Anneliese von Mayrhauser; Andre Bai; Tom Chen 001; Charles Anderson 001; Amjad Hajjar (HASE, 1998)

Multivariate autoregressive models for classification of spontaneous electroencephalographic signals during mental tasks. - Charles W. Anderson; Erik A. Stolz; Sanyogita Shamsunder (IEEE Trans. Biomed. Eng., 1998)

How Much Testing is Enough? Applying Stopping Rules to Behavioral Model Testing. - Tom Chen 001; Anneliese von Mayrhauser; Amjad Hajjar; Charles Anderson 001; Mehmet Sahinoglu (HASE, 1999)

Identifying Mental Tasks from Spontaneous EEG: Signal Representation and Spatial Analysis. - Charles W. Anderson (IWANN (2), 1999)

Using Temporal Neighborhoods to Adapt Function Approximators in Reinforcement Learning. - R. Matthew Kretchmar; Charles W. Anderson (IWANN (1), 1999)

EEG-based Cognitive Task Classification with ICA and Neural Networks. - David A. Peterson; Charles W. Anderson (IWANN (2), 1999)

On choosing test criteria for behavioral level hardware design verification. - Anneliese von Mayrhauser; Tom Chen 001; Jan Kok; Chuck Anderson 001; Anita Read; Amjad Hajjar (HLDVT, 2000)

Behavioral Cloning of Student Pilots with Modular Neural Networks. - Charles W. Anderson; Bruce A. Draper; David A. Peterson (ICML, 2000)

Achieving the Quality of Verification for Behavioral Models with Minimum Effort. - Tom Chen 001; Anneliese von Mayrhauser; Amjad Hajjar; Charles Anderson 001; Mehmet Sahinoglu (ISQED, 2000)

Robust reinforcement learning control. - R. Matthew Kretchmar; Peter Michael Young; Charles W. Anderson; Douglas C. Hittle; Michael L. Anderson; Christopher C. Delnero (ACC, 2001)

MIMO robust control for heating, ventilating and air conditioning (HVAC) systems. - Michael L. Anderson; Peter Michael Young; Douglas C. Hittle; Charles Anderson 001; Jililn Tu; David Hodgson (CDC, 2002)

Fast Anti-Random (FAR) Test Generation to Improve the Quality of Behavioral Model Verification. - Tom Chen 001; Andre Bai; Amjad Hajjar; Anneliese Amschler Andrews; Charles Anderson 001 (J. Electron. Test., 2002)

EEG Subspace Representations and Feature Selection for Brain-Computer Interfaces. - Charles W. Anderson; Michael J. Kirby (CVPR Workshops, 2003)

Modeling reward functions for incomplete state representations via echo state networks. - Keith Bush; Charles Anderson 001 (IJCNN, 2005)

Feature Selection and Blind Source Separation in an EEG-Based Brain-Computer Interface. - David A. Peterson; James N. Knight; Michael J. Kirby; Charles W. Anderson; Michael H. Thaut (EURASIP J. Adv. Signal Process., 2005)

Optimizing conductance parameters of cortical neural models via electrotonic partitions. - Keith Bush; James F. Knight; Charles Anderson 001 (Neural Networks, 2005)

Robust Reinforcement Learning Control Using Integral Quadratic Constraints for Recurrent Neural Networks. - Charles W. Anderson; Peter Michael Young; Michael R. Buehner; James N. Knight; K. A. Bush; Douglas C. Hittle (IEEE Trans. Neural Networks, 2007)

Restricted gradient-descent algorithm for value-function approximation in reinforcement learning. - André da Motta Salles Barreto; Charles W. Anderson (Artif. Intell., 2008)

MIMO Robust Control for HVAC Systems. - Michael Anderson; Michael R. Buehner; Peter Michael Young; Douglas C. Hittle; Charles Anderson 001; Jilin Tu; David Hodgson (IEEE Trans. Control. Syst. Technol., 2008)

Automatic creation of tile size selection models. - Tomofumi Yuki; Lakshminarayanan Renganarayanan; Sanjay V. Rajopadhye; Charles Anderson 001; Alexandre E. Eichenberger; Kevin O'Brien (CGO, 2010)

Analyzing Electroencephalograms Using Cloud Computing Techniques. - Kathleen Ericson; Shrideep Pallickara; Charles W. Anderson (CloudCom, 2010)

Dissociating the contributions of independent corticostriatal systems to visual categorization learning through the use of reinforcement learning modeling and Granger causality modeling. - Carol A. Seger; Erik J. Peterson; Corinna M. Cincotta; Dan Lopez-Paniagua; Charles W. Anderson (NeuroImage, 2010)

Discount and speed/execution tradeoffs in Markov Decision Process games. - Reinaldo Uribe; Fernando Lozano; Katsunari Shibata; Charles Anderson 001 (CIG, 2011)

Comparison of EEG blind source separation techniques to improve the classification of P300 trials. - Zach Cashero; Chuck Anderson 001 (EMBC, 2011)

Classification of EEG during imagined mental tasks by forecasting with Elman Recurrent Neural Networks. - Elliott M. Forney; Charles W. Anderson (IJCNN, 2011)

Hurricane Prediction with Python. - Minwoo Lee 001; Charles W. Anderson; Mark DeMaria (SciPy, 2011)

Exploiting spatiotemporal and device contexts for energy-efficient mobile embedded systems. - Brad K. Donohoo; Chris Ohlsen; Sudeep Pasricha; Charles Anderson 001 (DAC, 2012)

EEG character identification using stimulus sequences designed to maximize mimimal hamming distance. - Tadanori Fukami; Takamasa Shimada; Elliott M. Forney; Charles W. Anderson (EMBC, 2012)

Editorial A Successful Change From TNN to TNNLS and a Very Successful Year. - Derong Liu 001; Charles Anderson 001; Ahmad Taher Azar; Giorgio Battistelli; Eduardo Bayro-Corrochano; Cristiano Cervellera; David A. Elizondo; Maurizio Filippone; Giorgio Gnecco; Xiaolin Hu; Tingwen Huang; Weifeng Liu 001; et al. (IEEE Trans. Neural Networks Learn. Syst., 2013)

Using supervised training signals of observable state dynamics to speed-up and improve reinforcement learning. - Daniel L. Elliott; Charles Anderson 001 (ADPRL, 2014)

Convergent reinforcement learning control with neural networks and continuous action search. - Minwoo Lee 001; Charles W. Anderson (ADPRL, 2014)

EEG subspace analysis and classification using principal angles for Brain-Computer Interfaces. - Rehab Ashari; Charles Anderson 001 (CIBCI, 2014)

Context-Aware Energy Enhancements for Smart Mobile Devices. - Brad K. Donohoo; Chris Ohlsen; Sudeep Pasricha; Yi Xiang; Charles Anderson 001 (IEEE Trans. Mob. Comput., 2014)

LearnLoc: A framework for smart indoor localization with embedded mobile devices. - Sudeep Pasricha; Viney Ugave; Charles W. Anderson; Qi Han 001 (CODES+ISSS, 2015)

Faster reinforcement learning after pretraining deep networks to predict state dynamics. - Charles W. Anderson; Minwoo Lee 001; Daniel L. Elliott (IJCNN, 2015)

Failure-resilient real-time processing of health streams. - Kathleen Ericson; Shrideep Pallickara; Charles W. Anderson (Concurr. Comput. Pract. Exp., 2015)

Optimal Nudging: Solving Average-Reward Semi-Markov Decision Processes as a Minimal Sequence of Cumulative Tasks. - Reinaldo Uribe Muriel; Fernando Lozano; Charles Anderson 001 (CoRR, 2015)

To Fear or Not to Fear That is the Question: Code Characteristics of a Vulnerable Functionwith an Existing Exploit. - Awad A. Younis; Yashwant K. Malaiya; Charles Anderson 001; Indrajit Ray (CODASPY, 2016)

Relevance Vector Sampling for Reinforcement Learning in Continuous Action Space. - Minwoo Lee 001; Charles W. Anderson (ICMLA, 2016)

Proceedings of the 1st International Workshop on Robot Learning and Planning (RLP 2016). - Nancy M. Amato; Charles Anderson 001; Gregory S. Chirikjian; Hamidreza Chitsaz; Vishnu R. Desaraju; Chinwe Ekenna; Kris K. Hauser; Geoffrey A. Hollinger; Reza Iraji; Minwoo Lee 001; Qianli Ma 002; Seth McCammon; et al. (CoRR, 2016)

Can a reinforcement learning agent practice before it starts learning? - Minwoo Lee 001; Charles W. Anderson (IJCNN, 2017)

Networked by Design: Interventions for Teachers to Develop Social Capital. - Susan A. Yoon; Charles W. Anderson; Kira J. Baker-Doyle; Maarten de Laat; Elizabeth Xeng de los Santos; Kenneth A. Frank; Megan Hopkins; Qinyun Lin; Stefanie Marshall; Katie A. Miller; Femke Nijland; William R. Penuel; et al. (ICLS, 2018)

Advancing the Rehabilitative and Therapeutic Potential of BCI and Noninvasive Sensing Systems. - Stephanie M. Scott; Chris Raftery; Charles Anderson 001 (Brain Art, 2019)

Adversarial Sampling Attacks Against Phishing Detection. - Hossein Shirazi; Bruhadeshwar Bezawada; Indrakshi Ray; Charles Anderson 001 (DBSec, 2019)

Using Machine Learning to Detect Anomalies in Embedded Networks in Heavy Vehicles. - Hossein Shirazi; Indrakshi Ray; Charles Anderson 001 (FPS, 2019)

AI Assisted Annotator using Reinforcement Learning. - V. Ratna Saripalli; Gopal Avinash; Charles W. Anderson (CoRR, 2019)

Classifying environmental features from local observations of emergent swarm behavior. - Megan Emmons; Anthony A. Maciejewski; Charles Anderson 001; Edwin K. P. Chong (IEEE CAA J. Autom. Sinica, 2020)

Gradient boosting in crowd ensembles for Q-learning using weight sharing. - Daniel L. Elliott; KC Santosh; Charles Anderson 001 (Int. J. Mach. Learn. Cybern., 2020)

AI-Assisted Annotator Using Reinforcement Learning. - V. Ratna Saripalli; Dibyajyoti Pati; Michael Potter; Gopal Avinash; Charles W. Anderson (SN Comput. Sci., 2020)

Increased Reinforcement Learning Performance through Transfer of Representation Learned by State Prediction Model. - Alperen Tercan; Charles W. Anderson (IJCNN, 2021)

A Comparison of Conventional and Tri-Polar EEG Electrodes for Decoding Real and Imaginary Finger Movements from One Hand. - Saleh I. Alzahrani; Charles W. Anderson (Int. J. Neural Syst., 2021)

Directed adversarial sampling attacks on phishing detection. - Hossein Shirazi; Bruhadeshwar Bezawada; Indrakshi Ray; Chuck Anderson 001 (J. Comput. Secur., 2021)

Looking Back on the Actor-Critic Architecture. - Andrew G. Barto; Richard S. Sutton; Charles W. Anderson (IEEE Trans. Syst. Man Cybern. Syst., 2021)

Trainable Wavelet Neural Network for Non-Stationary Signals. - Jason Stock; Chuck Anderson 001 (CoRR, 2022)

Interpretable Climate Change Modeling With Progressive Cascade Networks. - Charles Anderson 001; Jason Stock; David Anderson (CoRR, 2022)

Attention-Based Scattering Network for Satellite Imagery. - Jason Stock; Chuck Anderson 001 (CoRR, 2022)

An Interpretable Model of Climate Change Using Correlative Learning. - Charles W. Anderson; Jason Stock (CoRR, 2022)

Memory-Based Sequential Attention. - Jason Stock; Charles Anderson 001 (Gaze Meets ML, 2023)

The Wisdom of the Crowd: Reliable Deep Reinforcement Learning Through Ensembles of Q-Functions. - Daniel L. Elliott; Charles W. Anderson (IEEE Trans. Neural Networks Learn. Syst., 2023)

SRViT: Vision Transformers for Estimating Radar Reflectivity from Satellite Observations at Scale. - Jason Stock; Kyle Hilburn; Imme Ebert-Uphoff; Charles W. Anderson (CoRR, 2024)