Balancing Specificity and Generality in a Panmictic-Based Rule-Discovery Learning Classifier System. - William N. L. Browne (IWLCS, 2002)

An abstraction agorithm for genetics-based reinforcement learning. - William N. L. Browne; Dan Scott 002 (GECCO, 2005)

An autonomous explore/exploit strategy. - Alex McMahon; Dan Scott 002; William N. L. Browne (GECCO Workshops, 2005)

Uncanny valley revisited. - F. C. Gee; Will N. Browne; Kazuhiko Kawamura (RO-MAN, 2005)

A Knowledge-Based Evolution Strategy for the Multi-Objective Minimum Spanning Tree Problem. - Madeleine Davis-Moradkhan; Will N. Browne (IEEE Congress on Evolutionary Computation, 2006)

Training Reformulated Product Units in Hybrid Neural Networks. - Philip T. Elliott; Diven Topiwala; Will N. Browne (IJCNN, 2006)

Knowledge-elicitation and data-mining: Fusing human and industrial plant information. - Will N. Browne; L. Yao; Ian Postlethwaite; S. Lowes; M. Mar (Eng. Appl. Artif. Intell., 2006)

Investigating scaling of an abstracted LCS utilising ternary and s-expression alphabets. - Will N. Browne; Charalambos Ioannides (GECCO (Companion), 2007)

The Role of Algorithms in Profiling. - Bernhard Anrig; Will N. Browne; Mark Gasson (Profiling the European Citizen, 2008)

A Hybridised Evolutionary Algorithm for Multi-Criterion Minimum Spanning Tree Problems. - Madeleine Davis-Moradkhan; Will N. Browne (HIS, 2008)

Consumer Robotic Products. - Jim Wyatt; Will N. Browne; Mark Gasson; Kevin Warwick (IEEE Robotics Autom. Mag., 2008)

Improving Evolutionary Computation Based Data-Mining for the Process Industry: The Importance of Abstraction. - William N. L. Browne (Learning Classifier Systems in Data Mining, 2008)

Memory-Based Cognitive Framework: A Low-Level Association Approach to Cognitive Architectures. - Paul Baxter 001; Will N. Browne (ECAL (1), 2009)

Extending evolutionary algorithms to discover tri-criterion and non-supported solutions for the minimum spanning tree problem. - Madeleine Davis-Moradkhan; Will N. Browne; Peter Grindrod (GECCO, 2009)

Cognitive Robotics. - Kazuhiko Kawamura; Will N. Browne (Encyclopedia of Complexity and Systems Science, 2009)

Sampling Methods in Genetic Programming for Classification with Unbalanced Data. - Rachel Hunt 001; Mark Johnston; Will N. Browne; Mengjie Zhang 001 (Australasian Conference on Artificial Intelligence, 2010)

Evolution of aesthetically pleasing images without human-in-the-loop. - Daniel L. Atkins; Roman Klapaukh; Will N. Browne; Mengjie Zhang 001 (IEEE Congress on Evolutionary Computation, 2010)

Using unrestricted loops in genetic programming for image classification. - Jan Larres; Mengjie Zhang 001; Will N. Browne (IEEE Congress on Evolutionary Computation, 2010)

Memory as the Substrate of Cognition: A Developmental Cognitive Robotics Perspective. - Paul Baxter 001; Will N. Browne (EpiRob, 2010)

New crossover operators in linear genetic programming for multiclass object classification. - Carlton Downey; Mengjie Zhang 001; Will N. Browne (GECCO, 2010)

Particle swarm optimisation for outlier detection. - Ammar W. Mohemmed; Mengjie Zhang 001; Will N. Browne (GECCO, 2010)

Engaging Robots: Innovative Outreach for Attracting Cybernetics Students. - Richard J. Mitchell 001; Kevin Warwick; Will N. Browne; Mark Gasson; Jim Wyatt (IEEE Trans. Educ., 2010)

Transparent, Online Image Pattern Classification Using a Learning Classifier System. - Ignas Kukenys; Will N. Browne; Mengjie Zhang 001 (EvoApplications (1), 2011)

Automatically defined functions for learning classifier systems. - Muhammad Iqbal 001; Mengjie Zhang 001; Will N. Browne (GECCO (Companion), 2011)

Confusion matrices for improving performance of feature pattern classifier systems. - Ignas Kukenys; Will N. Browne; Mengjie Zhang 001 (GECCO (Companion), 2011)

Developing an evolvable pattern generator using learning classifier systems. - Syahaneim Marzukhi; Will N. Browne; Mengjie Zhang 001 (ICARA, 2011)

Single Feature Ranking and Binary Particle Swarm Optimisation Based Feature Subset Ranking for Feature Selection. - Bing Xue 001; Mengjie Zhang 001; Will N. Browne (ACSC, 2012)

XCSR with Computed Continuous Action. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Australasian Conference on Artificial Intelligence, 2012)

Integration of Learning Classifier Systems with simultaneous localisation and mapping for autonomous robotics. - Henry Williams; Will N. Browne (IEEE Congress on Evolutionary Computation, 2012)

New fitness functions in binary particle swarm optimisation for feature selection. - Bing Xue 001; Mengjie Zhang 001; Will N. Browne (IEEE Congress on Evolutionary Computation, 2012)

Prediction of success in engineering study. - Dale A. Carnegie; Craig A. Watterson; Peter Andreae; Will N. Browne (EDUCON, 2012)

Strategies to improve engineering retention. - Dale A. Carnegie; Craig A. Watterson; Will N. Browne; James MacKay; Mel Lock; John Williams 003; Michael Forret (EDUCON, 2012)

XCS-based versus UCS-based feature pattern classification system. - Toktam Ebadi; Mengjie Zhang 001; Will N. Browne (GECCO, 2012)

Extracting and using building blocks of knowledge in learning classifier systems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (GECCO, 2012)

Two-cornered learning classifier systems for pattern generation and classification. - Syahaneim Marzukhi; Will N. Browne; Mengjie Zhang 001 (GECCO, 2012)

Multi-objective particle swarm optimisation (PSO) for feature selection. - Bing Xue 001; Mengjie Zhang 001; Will N. Browne (GECCO, 2012)

A multi-objective particle swarm optimisation for filter-based feature selection in classification problems. - Bing Xue 001; Liam Cervante; Lin Shang 001; Will N. Browne; Mengjie Zhang 001 (Connect. Sci., 2012)

Learning overlapping natured and niche imbalance boolean problems using XCS classifier systems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (IEEE Congress on Evolutionary Computation, 2013)

The effect of primitive sets on the expression of evolved images. - Roman Klapaukh; Will N. Browne; Mengjie Zhang 001 (IEEE Congress on Evolutionary Computation, 2013)

Optimizing visual attention models for predicting human fixations using Genetic Algorithms. - Syed Saud Naqvi; Will N. Browne; Christopher Hollitt (IEEE Congress on Evolutionary Computation, 2013)

Evolutionary spatial auto-correlation for assessing earthquake liquefaction potential using Parallel Linear Genetic Programming. - Aaron Scoble; Will N. Browne; Bill Stephenson; Zane Bruce; Mengjie Zhang 001 (IEEE Congress on Evolutionary Computation, 2013)

Novel Initialisation and Updating Mechanisms in PSO for Feature Selection in Classification. - Bing Xue 001; Mengjie Zhang 001; Will N. Browne (EvoApplications, 2013)

Learning classifier systems: introducing the user-friendly textbook. - Will N. Browne; Ryan J. Urbanowicz (GECCO (Companion), 2013)

Extending learning classifier system with cyclic graphs for scalability on complex, large-scale boolean problems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (GECCO, 2013)

Comparison of two methods for computing action values in XCS with code-fragment actions. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (GECCO (Companion), 2013)

Adaptive artificial datasets to discover the effects of domain features for classification tasks. - Syahaneim Marzukhi; Will N. Browne; Mengjie Zhang 001 (GECCO (Companion), 2013)

PSO for feature construction and binary classification. - Bing Xue 001; Mengjie Zhang 001; Yan Dai 007; Will N. Browne (GECCO, 2013)

Trading off salience and uncertainty in sampling a visual scene. - Arindam Bhakta; Marcus Frean; Christopher Hollitt; Will N. Browne (IVCNZ, 2013)

Combining object-based local and global feature statistics for salient object search. - Syed Saud Naqvi; Will N. Browne; Christopher Hollitt (IVCNZ, 2013)

Learning complex, overlapping and niche imbalance Boolean problems using XCS-based classifier systems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Evol. Intell., 2013)

Adaptive artificial datasets through learning classifier systems for classification tasks. - Syahaneim Marzukhi; Will N. Browne; Mengjie Zhang 001 (Evol. Intell., 2013)

Multi-objective Evolutionary Algorithms for filter Based Feature Selection in Classification. - Bing Xue 001; Liam Cervante; Lin Shang 001; Will N. Browne; Mengjie Zhang 001 (Int. J. Artif. Intell. Tools, 2013)

Evolving optimum populations with XCS classifier systems - XCS with code fragmented action. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Soft Comput., 2013)

Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach. - Bing Xue 001; Mengjie Zhang 001; Will N. Browne (IEEE Trans. Cybern., 2013)

Genetic algorithms based feature combination for salient object detection, for autonomously identified image domain types. - Syed Saud Naqvi; Will N. Browne; Christopher Hollitt (IEEE Congress on Evolutionary Computation, 2014)

Factors that affect the design of a successful engineering programme: A case study. - Dale A. Carnegie; Will N. Browne (EDUCON, 2014)

Salient object detection using learning classifiersystems that compute action mappings. - Muhammad Iqbal 001; Syed Saud Naqvi; Will N. Browne; Christopher Hollitt; Mengjie Zhang 001 (GECCO, 2014)

Reusing learned functionality in XCS: code fragments with constructed functionality and constructed features. - Isidro M. Alvarez; Will N. Browne; Mengjie Zhang 001 (GECCO (Companion), 2014)

Three-cornered coevolution learning classifier systems for classification tasks. - Syahaneim Marzukhi; Will N. Browne; Mengjie Zhang 001 (GECCO, 2014)

Reusing Learned Functionality to Address Complex Boolean Functions. - Isidro M. Alvarez; Will N. Browne; Mengjie Zhang 001 (SEAL, 2014)

Image Segmentation: A Survey of Methods Based on Evolutionary Computation. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (SEAL, 2014)

Evolutionary Feature Combination Based Seed Learning for Diffusion-Based Saliency. - Syed Saud Naqvi; Will N. Browne; Christopher Hollitt (SEAL, 2014)

Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms. - Bing Xue 001; Mengjie Zhang 001; Will N. Browne (Appl. Soft Comput., 2014)

Human-Interpretable Feature Pattern Classification System Using Learning Classifier Systems. - Toktam Ebadi; Ignas Kukenys; Will N. Browne; Mengjie Zhang 001 (Evol. Comput., 2014)

Binary PSO and Rough Set Theory for Feature Selection: a Multi-objective filter Based Approach. - Bing Xue 001; Liam Cervante; Lin Shang 001; Will N. Browne; Mengjie Zhang 001 (Int. J. Comput. Intell. Appl., 2014)

Reusing Building Blocks of Extracted Knowledge to Solve Complex, Large-Scale Boolean Problems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (IEEE Trans. Evol. Comput., 2014)

How should Learning Classifier Systems cover a state-action space? - Masaya Nakata; Pier Luca Lanzi; Tim Kovacs; Will Neil Browne; Keiki Takadama (CEC, 2015)

Emotion inspired adaptive robotic path planning. - Henry Williams; Christopher P. Lee-Johnson; Will N. Browne; Dale A. Carnegie (CEC, 2015)

A Supervised Figure-Ground Segmentation Method Using Genetic Programming. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (EvoApplications, 2015)

Back to the Future: Learning Classifier Systems as Cognitive Systems. - Will N. Browne (GECCO (Companion), 2015)

Introducing Rule-based Machine Learning: A Practical Guide. - Ryan J. Urbanowicz; Will N. Browne (GECCO (Companion), 2015)

Accurate marker based distance measurement with single camera. - A. Roberts; Will N. Browne; Christopher Hollitt (IVCNZ, 2015)

Introduction of a human based attention model for robotic navigation. - Henry Williams; Syed Saud Naqvi; Will N. Browne; Christopher Hollitt (IVCNZ, 2015)

An on-line Pittsburgh LCS for the Three-Cornered Coevolution Framework. - Syahaneim Marzukhi; Will N. Browne; Mengjie Zhang 001 (Evol. Intell., 2015)

A Comprehensive Comparison on Evolutionary Feature Selection Approaches to Classification. - Bing Xue 001; Mengjie Zhang 001; Will N. Browne (Int. J. Comput. Intell. Appl., 2015)

Improving genetic search in XCS-based classifier systems through understanding the evolvability of classifier rules. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Soft Comput., 2015)

Compaction for Code Fragment Based Learning Classifier Systems. - Isidro M. Alvarez; Will N. Browne; Mengjie Zhang 001 (ACALCI, 2016)

Multi-objective Genetic Programming for Figure-Ground Image Segmentation. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (ACALCI, 2016)

Compaction for code fragment based learning classifier systems - Redux. - Isidro M. Alvarez; Will N. Browne; Mengjie Zhang 001 (CEC, 2016)

Figure-ground image segmentation using genetic programming and feature selection. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (CEC, 2016)

Integration of code-fragment based learning classifier systems for multiple domain perception and learning. - Yi Liu 090; Muhammad Iqbal 001; Isidro M. Alvarez; Will N. Browne (CEC, 2016)

Adapting learning classifier systems to symbolic regression. - Syed Saud Naqvi; Will N. Browne (CEC, 2016)

A comprehensive strategy for mammogram image classification using learning classifier systems. - Abubakar Siddique; Muhammad Iqbal 001; Will N. Browne (CEC, 2016)

Human-inspired Scaling in Learning Classifier Systems: Case Study on the n-bit Multiplexer Problem Set. - Isidro M. Alvarez; Will N. Browne; Mengjie Zhang 001 (GECCO, 2016)

Code Fragments: Past and Future use in Transfer Learning. - Will N. Browne (GECCO (Companion), 2016)

Hands-on Workshop on Learning Classifier Systems. - Ryan J. Urbanowicz; Will N. Browne; Karthik Kuber (GECCO (Companion), 2016)

Proceedings in Adaptation, Learning and Optimization. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (IES, 2016)

Learning feature fusion strategies for various image types to detect salient objects. - Muhammad Iqbal 001; Syed Saud Naqvi; Will N. Browne; Christopher Hollitt; Mengjie Zhang 001 (Pattern Recognit., 2016)

Salient object detection via spectral matting. - Syed Saud Naqvi; Will N. Browne; Christopher Hollitt (Pattern Recognit., 2016)

A Survey on Evolutionary Computation Approaches to Feature Selection. - Bing Xue 001; Mengjie Zhang 001; Will N. Browne; Xin Yao 001 (IEEE Trans. Evol. Comput., 2016)

Feature Quality-Based Dynamic Feature Selection for Improving Salient Object Detection. - Syed Saud Naqvi; Will N. Browne; Christopher Hollitt (IEEE Trans. Image Process., 2016)

Wrapper Feature Construction for Figure-Ground Image Segmentation Using Genetic Programming. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (ACALCI, 2017)

SILVEREYE - The Implementation of Particle Swarm Optimization Algorithm in a Design Optimization Tool. - Judyta M. Cichocka; Agata Migalska; Will N. Browne; Edgar Rodriguez (CAAD Futures, 2017)

Learning figure-ground image segmentors by genetic programming. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (GECCO (Companion), 2017)

Theoretical XCS parameter settings of learning accurate classifiers. - Masaya Nakata; Will N. Browne; Tomoki Hamagami; Keiki Takadama (GECCO, 2017)

Visualisation and Optimisation of Learning Classifier Systems for Multiple Domain Learning. - Yi Liu 090; Bing Xue 001; Will N. Browne (SEAL, 2017)

Genetic programming for evolving figure-ground segmentors from multiple features. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (Appl. Soft Comput., 2017)

Learned Action SLAM: Sharing SLAM through learned path planning information between heterogeneous robotic platforms. - Henry Williams; Will N. Browne; Dale A. Carnegie (Appl. Soft Comput., 2017)

Image feature selection using genetic programming for figure-ground segmentation. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (Eng. Appl. Artif. Intell., 2017)

Extending XCS with Cyclic Graphs for Scalability on Complex Boolean Problems. - Muhammad Iqbal 001; Will N. Browne; Mengjie Zhang 001 (Evol. Comput., 2017)

Introduction to Learning Classifier Systems - Ryan J. Urbanowicz; Will N. Browne (Springer, 2017)

Hierarchical Learning Classifier Systems for Polymorphism in Heterogeneous Niches. - Yi Liu 090; Will N. Browne; Bing Xue 001 (Australasian Conference on Artificial Intelligence, 2018)

Decomposition Based Multi-Objective Evolutionary Algorithm in XCS for Multi-Objective Reinforcement Learning. - Xiu Cheng; Will N. Browne; Mengjie Zhang 001 (CEC, 2018)

Adapting Bagging and Boosting to Learning Classifier Systems. - Yi Liu 090; Will N. Browne; Bing Xue 001 (EvoApplications, 2018)

Theoretical adaptation of multiple rule-generation in XCS. - Masaya Nakata; Will N. Browne; Tomoki Hamagami (GECCO, 2018)

Tutorials at PPSN 2018. - Gisele Lobo Pappa; Michael T. M. Emmerich; Ana L. C. Bazzan; Will N. Browne; Kalyanmoy Deb; Carola Doerr; Marko Durasevic; Michael G. Epitropakis; Saemundur O. Haraldsson; Domagoj Jakobovic; Pascal Kerschke; Krzysztof Krawiec; et al. (PPSN (2), 2018)

Online Feature-Generation of Code Fragments for XCS to Guide Feature Construction. - Trung B. Nguyen; Will N. Browne; Mengjie Zhang 001 (CEC, 2019)

XCS with Combined Reward Method (XCSCR) for Policy Search in Multistep Problems. - Zheming Zhang; Will N. Browne; Dale A. Carnegie (CEC, 2019)

Absumption to complement subsumption in learning classifier systems. - Yi Liu 090; Will N. Browne; Bing Xue 001 (GECCO, 2019)

How XCS can prevent misdistinguishing rule accuracy: a preliminary study. - Masaya Nakata; Will Neil Browne (GECCO (Companion), 2019)

Improvement of code fragment fitness to guide feature construction in XCS. - Trung B. Nguyen; Will N. Browne; Mengjie Zhang 001 (GECCO, 2019)

Identifying Simple Shapes to Classify the Big Picture. - Megan Liang; Gabrielle Palado; Will N. Browne (IVCNZ, 2019)

Utility function generated saccade strategies for robot active vision: a probabilistic approach. - Arindam Bhakta; Christopher Hollitt; Will N. Browne; Marcus Frean (Auton. Robots, 2019)

Figure-ground image segmentation using feature-based multi-objective genetic programming techniques. - Yuyu Liang; Mengjie Zhang 001; Will N. Browne (Neural Comput. Appl., 2019)

A Memetic Algorithm for the Task Allocation Problem on Multi-robot Multi-point Dynamic Aggregation Missions. - Guanqiang Gao; Yi Mei 001; Bin Xin 002; Ya-Hui Jia; Will N. Browne (CEC, 2020)

Absumption and subsumption based learning classifier systems. - Yi Liu 090; Will N. Browne; Bing Xue 001 (GECCO, 2020)

Relatedness measures to aid the transfer of building blocks among multiple tasks. - Trung B. Nguyen; Will N. Browne; Mengjie Zhang 001 (GECCO, 2020)

Learning classifier systems: appreciating the lateralized approach. - Abubakar Siddique; Will N. Browne; Gina M. Grimshaw (GECCO Companion, 2020)

Lateralized learning for robustness against adversarial attacks in a visual classification system. - Abubakar Siddique; Will N. Browne; Gina M. Grimshaw (GECCO, 2020)

Emotion Categorization from Video-Frame Images Using a Novel Sequential Voting Technique. - Harisu Abdullahi Shehu; Will N. Browne; Hedwig Eisenbarth (ISVC (2), 2020)

An Adversarial Attacks Resistance-based Approach to Emotion Recognition from Images using Facial Landmarks. - Harisu Abdullahi Shehu; Will N. Browne; Hedwig Eisenbarth (RO-MAN, 2020)

Constructing Complexity-efficient Features in XCS with Tree-based Rule Conditions. - Trung B. Nguyen; Will N. Browne; Mengjie Zhang 001 (CEC, 2021)

Particle Swarm Optimization for Feature Selection in Emotion Categorization. - Harisu Abdullahi Shehu; Will N. Browne; Hedwig Eisenbarth (CEC, 2021)

Lateralized Approach for Robustness Against Attacks in Emotion Categorization from Images. - Harisu Abdullahi Shehu; Abubakar Siddique; Will N. Browne; Hedwig Eisenbarth (EvoApplications, 2021)

A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies. - Jordan T. Bishop; Marcus Gallagher; Will N. Browne (GECCO Companion, 2021)

Advanced Learning Classifier Systems. - Will N. Browne (GECCO Companion, 2021)

Adding a Computationally-Tractable Probabilistic Dimension to Meta-Heuristic-Based Microgrid Sizing. - Soheil Mohseni; Alan C. Brent; Daniel Burmester; Will N. Browne; Scott Kelly (TENCON, 2021)

An Out-of-Distribution Attack Resistance Approach to Emotion Categorization. - Harisu Abdullahi Shehu; Will N. Browne; Hedwig Eisenbarth (IEEE Trans. Artif. Intell., 2021)

Learning Optimality Theory for Accuracy-Based Learning Classifier Systems. - Masaya Nakata; Will N. Browne (IEEE Trans. Evol. Comput., 2021)

A Comparison of Learning Classifier Systems' Rule Compaction Algorithms for Knowledge Visualization. - Yi Liu 090; Will N. Browne; Bing Xue 001 (ACM Trans. Evol. Learn. Optim., 2021)

Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution. - Hayden Andersen; Andrew Lensen; Will N. Browne; Yi Mei 001 (CEC, 2022)

Improving the search of learning classifier systems through interpretable feature clustering. - Hayden Andersen; Andrew Lensen; Will N. Browne (GECCO Companion, 2022)

Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS. - Jordan T. Bishop; Marcus Gallagher; Will N. Browne (GECCO, 2022)

A comparison of rule compaction algorithms for michigan style learning classifier systems. - Yi Liu 090; Will N. Browne; Bing Xue 001 (GECCO Companion, 2022)

Learning classifier systems: cognitive inspired machine learning for eXplainable AI. - Abubakar Siddique; Will N. Browne (GECCO Companion, 2022)

An anti-attack method for emotion categorization from images. - Harisu Abdullahi Shehu; Will N. Browne; Hedwig Eisenbarth (Appl. Soft Comput., 2022)

A comparison of humans and machine learning classifiers categorizing emotion from faces with different coverings. - Harisu Abdullahi Shehu; Will N. Browne; Hedwig Eisenbarth (Appl. Soft Comput., 2022)

Visualizations for rule-based machine learning. - Yi Liu 090; Will N. Browne; Bing Xue 001 (Nat. Comput., 2022)

Adaptive Coordination Ant Colony Optimization for Multipoint Dynamic Aggregation. - Guanqiang Gao; Yi Mei 001; Ya-Hui Jia; Will N. Browne; Bin Xin 002 (IEEE Trans. Cybern., 2022)

Automated Coordination Strategy Design Using Genetic Programming for Dynamic Multipoint Dynamic Aggregation. - Guanqiang Gao; Yi Mei 001; Bin Xin 002; Ya-Hui Jia; Will N. Browne (IEEE Trans. Cybern., 2022)

Frames-of-Reference-Based Learning: Overcoming Perceptual Aliasing in Multistep Decision-Making Tasks. - Abubakar Siddique; Will N. Browne; Gina M. Grimshaw (IEEE Trans. Evol. Comput., 2022)

Producing Diverse Rashomon Sets of Counterfactual Explanations with Niching Particle Swarm Optimization Algorithms. - Hayden Andersen; Andrew Lensen; Will N. Browne; Yi Mei 001 (GECCO, 2023)

Absumption and Subsumption based Learning Classifier System for Real-World Continuous-based Problems. - Yi Liu 090; Yu Cui; Will N. Browne; Bing Xue 001; Wen Cheng; Yong Li; Lingfang Zeng (GECCO Companion, 2023)

Attention in Rule-Based Machine Learning: Exploiting Learning Classifier Systems' Generalization for Image Classification. - Abubakar Siddique; Muhammad Iqbal 001; Shahab Ud Din; Will N. Browne (GECCO Companion, 2023)

Modern Applications of Evolutionary Rule-based Machine Learning. - Abubakar Siddique; Will N. Browne; Ryan J. Urbanowicz (GECCO Companion, 2023)

Hierarchical Frames-of-References in Learning Classifier Systems. - Fumito Uwano; Will N. Browne (GECCO Companion, 2023)

Lateralized Learning for Multi-Class Visual Classification Tasks. - Abubakar Siddique; Will N. Browne; Gina M. Grimshaw (CoRR, 2023)

Lateralization in Agents' Decision Making: Evidence of Benefits/Costs from Artificial Intelligence. - Abubakar Siddique; Will N. Browne; Gina M. Grimshaw (CoRR, 2023)

Trajectory Tracking Control of Skid-Steering Mobile Robots with Slip and Skid Compensation using Sliding-Mode Control and Deep Learning. - Payam Nourizadeh; Fiona J. Stevens McFadden; Will N. Browne (CoRR, 2023)

Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection. - Nicolas Harvey Chapman; Feras Dayoub; Will N. Browne; Christopher F. Lehnert (IEEE Robotics Autom. Lett., 2023)

ConCS: A Continual Classifier System for Continual Learning of Multiple Boolean Problems. - Trung B. Nguyen; Will N. Browne; Mengjie Zhang 001 (IEEE Trans. Evol. Comput., 2023)

In situ slip estimation for mobile robots in outdoor environments. - Payam Nourizadeh; Fiona Stevens McFadden; Will N. Browne (J. Field Robotics, 2023)

Lateralized Learning to Solve Complex Boolean Problems. - Abubakar Siddique; Will N. Browne; Gina M. Grimshaw (IEEE Trans. Cybern., 2023)

Intepretable Local Explanations Through Genetic Programming. - Hayden Andersen; Andrew Lensen; Will N. Browne; Yi Mei 001 (GECCO Companion, 2024)

Learning Classifier Systems as a Solver for the Abstraction and Reasoning Corpus. - Cameron Coombe; David Howard 001; Will N. Browne (GECCO Companion, 2024)

A Phenotypic Learning Classifier System for Problems with Continuous Features. - Yi Liu 090; Yu Cui; Wen Cheng; Will Neil Browne; Bing Xue 001; Chengyuan Zhu; Yiding Zhang; Mingkai Sheng; Lingfang Zeng (GECCO, 2024)

Evolutionary Machine Learning for Interpretable and eXplainable AI. - Abubakar Siddique; Will N. Browne; Ryan J. Urbanowicz (GECCO Companion, 2024)

Cognitive Learning System for Sequential Aliasing Patterns of States in Multistep Decision-Making. - Fumito Uwano; Will Neil Browne (GECCO Companion, 2024)

Enhancing Visual Focus: Incorporating Attention into Rule-Based Machine Learning. - Abubakar Siddique; Muhammad Iqbal 001; Will N. Browne (IVCNZ, 2024)

Enhancing Embodied Object Detection through Language-Image Pre-training and Implicit Object Memory. - Nicolas Harvey Chapman; Feras Dayoub; Will N. Browne; Chris Lehnert (CoRR, 2024)

Open-Vocabulary Part-Based Grasping. - Tjeard van Oort; Dimity Miller; Will N. Browne; Nicolas Marticorena; Jesse Haviland; Niko Sünderhauf (CoRR, 2024)

In situ skid estimation for mobile robots in outdoor environments. - Payam Nourizadeh; Fiona J. Stevens McFadden; Will N. Browne (J. Field Robotics, 2024)

Attention-Based Methods for Emotion Categorization From Partially Covered Faces. - Harisu Abdullahi Shehu; Will N. Browne; Hedwig Eisenbarth (IEEE Trans. Emerg. Top. Comput. Intell., 2024)

Enhancing XCS with Dual-Stream Identification for Perceptual Aliasing in Multi-Step Decision-Making. - Fumito Uwano; Will N. Browne (GECCO, 2025)

Enhancing Embodied Object Detection with Spatial Feature Memory. - Nicolas Harvey Chapman; Christopher F. Lehnert; Will N. Browne; Feras Dayoub (WACV, 2025)

A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean Problems. - Isidro M. Alvarez; Trung B. Nguyen; Will N. Browne; Mengjie Zhang 001 (Evol. Comput., 2025)

Emotion categorization from facial expressions: A review of datasets, methods, and research directions. - Harisu Abdullahi Shehu; Will N. Browne; Hedwig Eisenbarth (Neurocomputing, 2025)

QueryAdapter: Rapid Adaptation of Vision-Language Models in Response to Natural Language Queries. - Nicolas Harvey Chapman; Feras Dayoub; Will N. Browne; Christopher F. Lehnert (CoRR, 2025)