Dependency Structures of Data Base Relationships. - William Ward Armstrong (IFIP Congress, 1974)

Adaptation Algorithms for Binary Tree Networks. - William W. Armstrong; Jan Gecsei (IEEE Trans. Syst. Man Cybern., 1979)

Decomposition and Functional Dependencies in Relations. - William Ward Armstrong; Claude Delobel (ACM Trans. Database Syst., 1980)

A Mixed-Flow Query Processing Strategy for a Multiprocessor Database System. - William Ward Armstrong; Ahmed S. Mohamed (ICDCS, 1985)

Solving equations of motion on a virtual tree machine. - William Ward Armstrong; T. Anthony Marsland; M. Olafsson; Jonathan Schaeffer 001 (PP, 1985)

The dynamics of articulated rigid bodies for purposes of animation. - William W. Armstrong; Mark W. Green 001 (Vis. Comput., 1985)

Near-Real-Time Control of Human Figure Models. - William W. Armstrong; Mark W. Green 001; Robert Lake (IEEE Computer Graphics and Applications, 1987)

Measuring learning progress in intelligent autonomous robots. - Ahmed S. Mohamed; William Ward Armstrong (J. Field Robotics, 1988)

Sensory nerve recording for closed-loop control to restore motor functions. - Dejan B. Popovic; Richard B. Stein; Ksenij Lj Jovanovic; Rongching Dai; Aleksandar Kostov; William W. Armstrong (IEEE Trans. Biomed. Eng., 1993)

Machine learning in control of functional electrical stimulation systems for locomotion. - Aleksandar Kostov; Brian J. Andrews; Dejan B. Popovic; Richard B. Stein; William W. Armstrong (IEEE Trans. Biomed. Eng., 1995)

Hardware Requirements for Fast Evaluation of Functions Learned by Adaptive Logic Networks. - William Ward Armstrong (ICES, 1996)

Adaptive Logic Networks for Facial Feature Detection. - Dmitry O. Gorodnichy; William Ward Armstrong; Xiaobo Li 001 (ICIAP (2), 1997)

Reinforcement Learning Applied to Simulated Basketball Balancing. - William W. Armstrong (NC, 1998)

A new technique for reinforcement learning for control. - William W. Armstrong; Darwin Li (SMC, 1998)

Reinforcement learning for autonomous robot navigation. - William Ward Armstrong; Brant Coghlan; Dmitry O. Gorodnichy (IJCNN, 1999)

Learning Hyperplane Tree: A Piecewise Linear and Fully Interpretable Decision-making Framework. - Hongyi Li; Jun Xu; William Ward Armstrong (CoRR, 2025)

LHT: Statistically-Driven Oblique Decision Trees for Interpretable Classification. - Hongyi Li; Jun Xu; William Ward Armstrong (CoRR, 2025)