Will N. Browne

发表

Learning classifier systems: introducing the user-friendly textbook

Will N. Browne, Ryan J. Urbanowicz, R. Urbanowicz, 2013, GECCO.

Feature Construction Using Genetic Programming for Figure-Ground Image Segmentation

Mengjie Zhang, Will N. Browne, Yuyu Liang, 2017 .

Developing an evolvable pattern generator using learning classifier systems

Mengjie Zhang, Will N. Browne, Syahaneim Marzukhi, 2011, The 5th International Conference on Automation, Robotics and Applications.

Factors that affect the design of a successful engineering programme: A case study

Dale Anthony Carnegie, Will N. Browne, D. Carnegie, 2014, 2014 IEEE Global Engineering Education Conference (EDUCON).

Memory as the Substrate of Cognition: A Developmental Cognitive Robotics Perspective

Paul Baxter, Will N. Browne, Paul E. Baxter, 2010, EpiRob.

Trading off salience and uncertainty in sampling a visual scene

Will N. Browne, Marcus Frean, Arindam Bhakta, 2013, 2013 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013).

Engaging Robots: Innovative Outreach for Attracting Cybernetics Students

Will N. Browne, Kevin Warwick, Richard J. Mitchell, 2010, IEEE Transactions on Education.

Adapting learning classifier systems to symbolic regression

Will N. Browne, Syed S. Naqvi, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Consumer Robotic Products

Will N. Browne, Kevin Warwick, Mark Gasson, 2008, IEEE Robotics & Automation Magazine.

Evolutionary spatial auto-correlation for assessing earthquake liquefaction potential using Parallel Linear Genetic Programming

Mengjie Zhang, Will N. Browne, Aaron Scoble, 2013, 2013 IEEE Congress on Evolutionary Computation.

New crossover operators in linear genetic programming for multiclass object classification

Mengjie Zhang, Will N. Browne, Carlton Downey, 2010, GECCO '10.

Cognitive Robotics

Kazuhiko Kawamura, Will N. Browne, G. Lakemeyer, 2022 .

Learned Action SLAM: Sharing SLAM through learned path planning information between heterogeneous robotic platforms

Dale Anthony Carnegie, Will N. Browne, Henry Williams, 2017, Appl. Soft Comput..

Proceedings in Adaptation, Learning and Optimization

Will N. Browne, Mengjie Zhang, Yuyu Liang, 2016, IES.

Extracting and using building blocks of knowledge in learning classifier systems

Mengjie Zhang, Will N. Browne, Muhammad Iqbal, 2012, GECCO '12.

Hierarchical Learning Classifier Systems for Polymorphism in Heterogeneous Niches

Bing Xue, Will N. Browne, Yi Liu, 2018, Australasian Conference on Artificial Intelligence.

Introduction to Learning Classifier Systems

Will N. Browne, Ryan J. Urbanowicz, R. Urbanowicz, 2017, SpringerBriefs in Intelligent Systems.

Investigating Scaling of an Abstracted LCS Utilising Ternary and S-Expression Alphabets

Will N. Browne, Charalambos Ioannides, 2007, IWLCS.

Human-Interpretable Feature Pattern Classification System Using Learning Classifier Systems

Mengjie Zhang, Toktam Ebadi, Will N. Browne, 2014, Evolutionary Computation.

Multi-objective particle swarm optimisation (PSO) for feature selection

Mengjie Zhang, Bing Xue, Will N. Browne, 2012, GECCO '12.

Constructing Complexity-efficient Features in XCS with Tree-based Rule Conditions pdf

Will N. Browne, Mengjie Zhang, Trung B. Nguyen, 2020, 2021 IEEE Congress on Evolutionary Computation (CEC).

The effect of primitive sets on the expression of evolved images

Mengjie Zhang, Will N. Browne, Roman Klapaukh, 2013, 2013 IEEE Congress on Evolutionary Computation.

Decomposition Based Multi-Objective Evolutionary Algorithm in XCS for Multi-Objective Reinforcement Learning

Mengjie Zhang, Will N. Browne, Xiu Cheng, 2018, 2018 IEEE Congress on Evolutionary Computation (CEC).

Strategies to improve engineering retention

Dale Anthony Carnegie, Will N. Browne, John Williams, 2012, Proceedings of the 2012 IEEE Global Engineering Education Conference (EDUCON).

Integration of Learning Classifier Systems with simultaneous localisation and mapping for autonomous robotics

Will N. Browne, Henry Williams, Henry Williams, 2012, 2012 IEEE Congress on Evolutionary Computation.

Using unrestricted loops in genetic programming for image classification

Mengjie Zhang, Will N. Browne, Jan Larres, 2010, IEEE Congress on Evolutionary Computation.

Wrapper Feature Construction for Figure-Ground Image Segmentation Using Genetic Programming

Mengjie Zhang, Will N. Browne, Yuyu Liang, 2017, ACALCI.

Figure-ground image segmentation using feature-based multi-objective genetic programming techniques

Mengjie Zhang, Will N. Browne, Yuyu Liang, 2017, Neural Computing and Applications.

Confusion matrices for improving performance of feature pattern classifier systems

Mengjie Zhang, Will N. Browne, Ignas Kukenys, 2011, GECCO '11.

Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms

Mengjie Zhang, Bing Xue, Will N. Browne, 2014, Appl. Soft Comput..

Human-inspired Scaling in Learning Classifier Systems: Case Study on the n-bit Multiplexer Problem Set

Mengjie Zhang, Will N. Browne, Isidro M. Alvarez, 2016, GECCO.

Uncanny valley revisited

Kazuhiko Kawamura, Will N. Browne, F. C. Gee, 2005, ROMAN 2005. IEEE International Workshop on Robot and Human Interactive Communication, 2005..

PSO for feature construction and binary classification

Mengjie Zhang, Bing Xue, Will N. Browne, 2013, GECCO '13.

Evolution of aesthetically pleasing images without human-in-the-loop

Mengjie Zhang, Will N. Browne, Roman Klapaukh, 2010, IEEE Congress on Evolutionary Computation.

Visualisation and Optimisation of Learning Classifier Systems for Multiple Domain Learning

Yi Liu, Bing Xue, Will N. Browne, 2017, SEAL.

Image Segmentation: A Survey of Methods Based on Evolutionary Computation

Mengjie Zhang, Will N. Browne, Yuyu Liang, 2014, SEAL.

Compaction for Code Fragment Based Learning Classifier Systems

Mengjie Zhang, Will N. Browne, Isidro M. Alvarez, 2016, ACALCI.

Sampling Methods in Genetic Programming for Classification with Unbalanced Data

Mark Johnston, Mengjie Zhang, Will N. Browne, 2010, Australasian Conference on Artificial Intelligence.

Evolutionary Feature Combination Based Seed Learning for Diffusion-Based Saliency

Will N. Browne, Christopher Hollitt, Syed Saud Naqvi, 2014, SEAL.

SILVEREYE – The Implementation of Particle Swarm Optimization Algorithm in a Design Optimization Tool

Will N. Browne, Edgar Rodriguez, Judyta M. Cichocka, 2017 .

Improvement of code fragment fitness to guide feature construction in XCS

Mengjie Zhang, Will N. Browne, Trung B. Nguyen, 2019, GECCO.

Memory-Based Cognitive Framework: A Low-Level Association Approach to Cognitive Architectures

Paul Baxter, Will N. Browne, Paul E. Baxter, 2009, ECAL.

A Comprehensive Comparison on Evolutionary Feature Selection Approaches to Classification

Mengjie Zhang, Bing Xue, Will N. Browne, 2015, Int. J. Comput. Intell. Appl..

A multi-objective particle swarm optimisation for filter-based feature selection in classification problems

Mengjie Zhang, Bing Xue, Will N. Browne, 2012, Connect. Sci..

Adaptive artificial datasets to discover the effects of domain features for classification tasks

Mengjie Zhang, Will N. Browne, Syahaneim Marzukhi, 2013, GECCO.

Absumption and subsumption based learning classifier systems

Will N. Browne, Bing Xue, Yi Liu, 2020, GECCO.

Introducing Rule-based Machine Learning: A Practical Guide

Will N. Browne, Ryan J. Urbanowicz, R. Urbanowicz, 2015, GECCO.

Salient object detection using learning classifiersystems that compute action mappings

Mengjie Zhang, Will N. Browne, Christopher Hollitt, 2014, GECCO.

Extending learning classifier system with cyclic graphs for scalability on complex, large-scale boolean problems

Mengjie Zhang, Will N. Browne, Muhammad Iqbal, 2013, GECCO '13.

An industrial Learning Classifier System: the importance of pre-processing real data and choice of alphabet

Will N. Browne, Karen Margaret Holford, John Bullock, 2000 .

Learning Optimality Theory for Accuracy-Based Learning Classifier Systems

Will N. Browne, Masaya Nakata, Masaya Nakata, 2020, IEEE Transactions on Evolutionary Computation.

Evolutionary Algorithms for the Multi Criterion Minimum Spanning Tree Problem

Will N. Browne, Madeleine Davis-Moradkhan, Madeleine Davis-Moradkhan, 2010 .

Three-cornered coevolution learning classifier systems for classification tasks

Mengjie Zhang, Will N. Browne, Syahaneim Marzukhi, 2014, GECCO.

Theoretical adaptation of multiple rule-generation in XCS

Will N. Browne, Masaya Nakata, Tomoki Hamagami, 2018, GECCO.

A Knowledge-Based Evolution Strategy for the Multi-Objective Minimum Spanning Tree Problem

Will N. Browne, Madeleine Davis-Moradkhan, Madeleine Davis-Moradkhan, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Extending evolutionary algorithms to discover tri-criterion and non-supported solutions for the minimum spanning tree problem

Peter Grindrod, Will N. Browne, Madeleine Davis-Moradkhan, 2009, GECCO.

Introduction of a human based attention model for robotic navigation

Will N. Browne, Christopher Hollitt, Syed Saud Naqvi, 2015, 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ).

Accurate marker based distance measurement with single camera

Will N. Browne, Christopher Hollitt, A. Roberts, 2015, 2015 International Conference on Image and Vision Computing New Zealand (IVCNZ).

Multi-objective Genetic Programming for Figure-Ground Image Segmentation

Mengjie Zhang, Will N. Browne, Yuyu Liang, 2016, ACALCI.

Compaction for code fragment based learning classifier systems — Redux

Mengjie Zhang, Will N. Browne, Isidro M. Alvarez, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Back to the Future: Learning Classifier Systems as Cognitive Systems

Will N. Browne, 2015, GECCO.

Tutorials at PPSN 2018

Roman Senkerik, Per Kristian Lehre, Pietro Simone Oliveto, 2018, PPSN.

Integration of code-fragment based learning classifier systems for multiple domain perception and learning

Yi Liu, Will N. Browne, Muhammad Iqbal, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Multi-objective Evolutionary Algorithms for filter Based Feature Selection in Classification

Mengjie Zhang, Bing Xue, Will N. Browne, 2013, Int. J. Artif. Intell. Tools.

XCS-based versus UCS-based feature pattern classification system

Mengjie Zhang, Toktam Ebadi, Will N. Browne, 2012, GECCO '12.

Automatically defined functions for learning classifier systems

Mengjie Zhang, Will N. Browne, Muhammad Iqbal, 2011, GECCO '11.

A Practical Application of a Learning Classifier System in a Steel Hot Strip Mill

Will N. Browne, Karen Margaret Holford, J. Bullock, 1997, ICANNGA.

Adaptive artificial datasets through learning classifier systems for classification tasks

Mengjie Zhang, Will N. Browne, Syahaneim Marzukhi, 2013, Evol. Intell..

The implementation of a learning classifier system for parameter identification by signal processing of data from steel strip downcoilers

Will N. Browne, Karen Margaret Holford, C. J. Moore, 1996 .

Theoretical XCS parameter settings of learning accurate classifiers

Will N. Browne, Masaya Nakata, Keiki Takadama, 2017, GECCO.

Reusing Learned Functionality to Address Complex Boolean Functions

Mengjie Zhang, Will N. Browne, Isidro M. Alvarez, 2014, SEAL.

Emotion inspired adaptive robotic path planning

Dale Anthony Carnegie, Will N. Browne, Christopher P. Lee-Johnson, 2015, 2015 IEEE Congress on Evolutionary Computation (CEC).

Learning overlapping natured and niche imbalance boolean problems using XCS classifier systems

Will N. Browne, Mengjie Zhang, Muhammad Iqbal, 2013, 2013 IEEE Congress on Evolutionary Computation.

Lateralized learning for robustness against adversarial attacks in a visual classification system

Will N. Browne, Gina M. Grimshaw, Abubakar Siddique, 2020, GECCO.

Will N. Browne, Mengjie Zhang, Trung B. Nguyen, 2020, GECCO.

Learning complex, overlapping and niche imbalance Boolean problems using XCS-based classifier systems

Mengjie Zhang, Will N. Browne, Muhammad Iqbal, 2013, Evol. Intell..

Adapting Bagging and Boosting to Learning Classifier Systems

Yi Liu, Bing Xue, Will N. Browne, 2018, EvoApplications.

Adaptive artificial datasets through learning classifier systems for classification tasks

Mengjie Zhang, Will N. Browne, Syahaneim Marzukhi, 2013, Evolutionary Intelligence.

Developing an emotion-based architecture for autonomous agents

Will N. Browne, C. Tingley, 2006 .

Investigating scaling of an abstracted LCS utilising ternary and s-expression alphabets

Will N. Browne, Charalambos Ioannides, 2007, GECCO '07.

Evolving optimum populations with XCS classifier systems

Mengjie Zhang, Will N. Browne, Muhammad Iqbal, 2012, Soft Computing.

Code Fragments: Past and Future use in Transfer Learning

Will N. Browne, 2016, GECCO.

Genetic programming for evolving figure-ground segmentors from multiple features

Mengjie Zhang, Will N. Browne, Yuyu Liang, 2017, Appl. Soft Comput..

Salient object detection via spectral matting

Will N. Browne, Christopher Hollitt, Syed Saud Naqvi, 2016, Pattern Recognit..

An on-line Pittsburgh LCS for the Three-Cornered Coevolution Framework

Mengjie Zhang, Will N. Browne, Syahaneim Marzukhi, 2015, Evolutionary Intelligence.

A Survey on Evolutionary Computation Approaches to Feature Selection

Xin Yao, Mengjie Zhang, Bing Xue, 2016, IEEE Transactions on Evolutionary Computation.

New fitness functions in binary particle swarm optimisation for feature selection

Mengjie Zhang, Bing Xue, Will N. Browne, 2012, 2012 IEEE Congress on Evolutionary Computation.

Binary PSO and Rough Set Theory for Feature Selection: a Multi-objective filter Based Approach

Mengjie Zhang, Bing Xue, Will N. Browne, 2014, Int. J. Comput. Intell. Appl..

An Industry-based Development of the Learning Classifier System Technique

Will N. Browne, Karen Margaret Holford, C. J. Moore, 2000 .

A Supervised Figure-Ground Segmentation Method Using Genetic Programming

Mengjie Zhang, Will N. Browne, Yuyu Liang, 2015, EvoApplications.

Image feature selection using genetic programming for figure-ground segmentation

Will N. Browne, Mengjie Zhang, Yuyu Liang, 2017, Eng. Appl. Artif. Intell..

Feature Quality-Based Dynamic Feature Selection for Improving Salient Object Detection

Will N. Browne, Christopher Hollitt, Syed Saud Naqvi, 2016, IEEE Transactions on Image Processing.

Genetic algorithms based feature combination for salient object detection, for autonomously identified image domain types

Will N. Browne, Christopher Hollitt, Syed Saud Naqvi, 2014, 2014 IEEE Congress on Evolutionary Computation (CEC).

Learning classifier systems: appreciating the lateralized approach

Will N. Browne, Gina M. Grimshaw, Abubakar Siddique, 2020, GECCO Companion.

Utility function generated saccade strategies for robot active vision: a probabilistic approach

Will N. Browne, Marcus Frean, Arindam Bhakta, 2018, Autonomous Robots.

Learning feature fusion strategies for various image types to detect salient objects

Mengjie Zhang, Will N. Browne, Christopher Hollitt, 2016, Pattern Recognit..

Comparison of two methods for computing action values in XCS with code-fragment actions

Mengjie Zhang, Will N. Browne, Muhammad Iqbal, 2013, GECCO.

Training Reformulated Product Units in Hybrid Neural Networks

Will N. Browne, Diven Topiwala, Philip T. Elliott, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Identifying Simple Shapes to Classify the Big Picture

Will N. Browne, Megan Liang, Gabrielle Palado, 2019, 2019 International Conference on Image and Vision Computing New Zealand (IVCNZ).

Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach

Mengjie Zhang, Bing Xue, Will N. Browne, 2013, IEEE Transactions on Cybernetics.

A comprehensive strategy for mammogram image classification using learning classifier systems

Will N. Browne, Abubakar Siddique, Muhammad Iqbal, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

The Role of Algorithms in Profiling

Will N. Browne, Mark Gasson, Bernhard Anrig, 2008, Profiling the European Citizen.

Absumption to complement subsumption in learning classifier systems

Bing Xue, Yi Liu, Will N. Browne, 2019, GECCO.

Single Feature Ranking and Binary Particle Swarm Optimisation Based Feature Subset Ranking for Feature Selection

Mengjie Zhang, Bing Xue, Will N. Browne, 2012, ACSC.

Novel Initialisation and Updating Mechanisms in PSO for Feature Selection in Classification

Mengjie Zhang, Bing Xue, Will N. Browne, 2013, EvoApplications.

Cybernetics and its application

Will N. Browne, William Harwin, Kevin Warwick, 2008 .

Learning figure-ground image segmentors by genetic programming

Mengjie Zhang, Will N. Browne, Yuyu Liang, 2017, GECCO.

Reusing Building Blocks of Extracted Knowledge to Solve Complex, Large-Scale Boolean Problems

Mengjie Zhang, Will N. Browne, Muhammad Iqbal, 2014, IEEE Transactions on Evolutionary Computation.

Figure-ground image segmentation using genetic programming and feature selection

Mengjie Zhang, Will N. Browne, Yuyu Liang, 2016, 2016 IEEE Congress on Evolutionary Computation (CEC).

Extending XCS with Cyclic Graphs for Scalability on Complex Boolean Problems

Will N. Browne, Mengjie Zhang, Muhammad Iqbal, 2017, Evolutionary Computation.

Reusing learned functionality in XCS: code fragments with constructed functionality and constructed features

Mengjie Zhang, Will N. Browne, Isidro M. Alvarez, 2014, GECCO.

Transparent, Online Image Pattern Classification Using a Learning Classifier System

Mengjie Zhang, Will N. Browne, Ignas Kukenys, 2011, EvoApplications.

A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean Problems pdf

Will N. Browne, Mengjie Zhang, Trung B. Nguyen, 2020, ArXiv.

Hands-on Workshop on Learning Classifier Systems

Will N. Browne, Ryan J. Urbanowicz, Karthik Kuber, 2016, GECCO.

Two-cornered learning classifier systems for pattern generation and classification

Mengjie Zhang, Will N. Browne, Syahaneim Marzukhi, 2012, GECCO '12.

A Hybridised Evolutionary Algorithm for Multi-Criterion Minimum Spanning Tree Problems

Will N. Browne, Madeleine Davis-Moradkhan, Madeleine Davis-Moradkhan, 2008, 2008 Eighth International Conference on Hybrid Intelligent Systems.

Optimizing visual attention models for predicting human fixations using Genetic Algorithms

Will N. Browne, Christopher Hollitt, Syed Saud Naqvi, 2013, 2013 IEEE Congress on Evolutionary Computation.

Improving genetic search in XCS-based classifier systems through understanding the evolvability of classifier rules

Mengjie Zhang, Will N. Browne, Muhammad Iqbal, 2015, Soft Comput..

Prediction of success in engineering study

Dale Anthony Carnegie, Will N. Browne, Peter Andreae, 2012, Proceedings of the 2012 IEEE Global Engineering Education Conference (EDUCON).

Combining object-based local and global feature statistics for salient object search

Will N. Browne, Christopher Hollitt, Syed Saud Naqvi, 2013, 2013 28th International Conference on Image and Vision Computing New Zealand (IVCNZ 2013).

Particle swarm optimisation for outlier detection

Mengjie Zhang, Will N. Browne, Ammar W. Mohemmed, 2010, GECCO '10.

XCSR with Computed Continuous Action

Mengjie Zhang, Will N. Browne, Muhammad Iqbal, 2012, Australasian Conference on Artificial Intelligence.

Strategic design optimisation of multi-energy-storage-technology micro-grids considering a two-stage game-theoretic market for demand response aggregation

Will N. Browne, Alan C. Brent, Scott Kelly, 2021 .

Particle Swarm Optimization for Feature Selection in Emotion Categorization

Will N. Browne, Harisu Abdullahi Shehu, Hedwig Eisenbarth, 2021, 2021 IEEE Congress on Evolutionary Computation (CEC).

A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies

Will N. Browne, Marcus Gallagher, Jordan T. Bishop, 2021, GECCO Companion.

Lateralized Approach for Robustness Against Attacks in Emotion Categorization from Images

Will N. Browne, Harisu Abdullahi Shehu, Hedwig Eisenbarth, 2021, EvoApplications.

Frames-of-Reference-Based Learning: Overcoming Perceptual Aliasing in Multistep Decision-Making Tasks

Will N. Browne, Gina M. Grimshaw, Abubakar Siddique, 2021, IEEE Transactions on Evolutionary Computation.

An Out-of-Distribution Attack Resistance Approach to Emotion Categorization

Will N. Browne, Harisu Abdullahi Shehu, Hedwig Eisenbarth, 2021, IEEE Transactions on Artificial Intelligence.

Modelling utility-aggregator-customer interactions in interruptible load programmes using non-cooperative game theory

Will N. Browne, Alan C. Brent, Scott Kelly, 2021 .

EMOTIONAL COGNITIVE STEPS TOWARDS CONSCIOUSNESS

Will N. Browne, Richard J. Hussey, 2009 .

A Game-Theoretic Approach to Model Interruptible Loads: Application to Micro-Grid Planning

Will N. Browne, A. Brent, Daniel Burmester, 2020, 2020 IEEE Power & Energy Society General Meeting (PESGM).

Visualizations for rule-based machine learning

Will N. Browne, Bing Xue, Yi Liu, 2021, Natural Computing.

swarm optimisation for feature selection in classification : ovel initialisation and updating mechanisms

Will N. Browne, Mengjie Zhang, ing Xue, 2014 .

An Autonomous Explore/Exploit Strategy in Mark Bishop and Slawek Nasuto, Exploration vs. Exploitation in Naturally Inspired Search, in Tim Kovacs and James Marshall

Paul Baxter, Will N. Browne, A. McMahon, 2006 .

Toward Evolutionary Design: First Steps

Will N. Browne, Paul Sharkey, Will N. Browne, 2004 .

Emotion Categorization from Faces of People with Sunglasses and Facemasks

Will N. Browne, H. Eisenbarth, H. Shehu, 2021 .

Automated Coordination Strategy Design Using Genetic Programming for Dynamic Multipoint Dynamic Aggregation

Will N. Browne, Bin Xin, Y. Mei, 2021, IEEE Transactions on Cybernetics.

Proceedings of the 10th International Conference on Simulated Evolution and Learning - Volume 8886

Grant Dick, Peter A. Whigham, Mengjie Zhang, 2014 .

An anti-attack method for emotion categorization from images

Will N. Browne, H. Eisenbarth, H. Shehu, 2022, Appl. Soft Comput..

Improving the search of learning classifier systems through interpretable feature clustering

Will N. Browne, Hayden Andersen, Andrew Lensen, 2022, GECCO Companion.

Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution

Will N. Browne, Y. Mei, Hayden Andersen, 2022, 2022 IEEE Congress on Evolutionary Computation (CEC).

A comparison of humans and machine learning classifiers categorizing emotion from faces with different coverings

Will N. Browne, H. Eisenbarth, H. Shehu, 2022, Appl. Soft Comput..

Utility function generated saccade strategies for robot active vision: a probabilistic approach

Will N. Browne, Marcus Frean, C. Hollitt, 2018, Autonomous Robots.

An Investigation of Primitive Set Selection and Evaluation for Image Generation Using Genetic Programming

Will N. Browne, Mengjie Zhang, R. Klapaukh, 2010 .

Visualizations for rule-based machine learning

Will N. Browne, Bing Xue, Yi Liu, 2021, Natural Computing.

Demand response-integrated investment and operational planning of renewable and sustainable energy systems considering forecast uncertainties: A systematic review

Will N. Browne, A. Brent, Soheil Mohseni, 2022, Renewable and Sustainable Energy Reviews.

Memory-based Embodied Cognition: a computational architecture

Paul Baxter, Will N. Browne, Will N. Browne, 2008 .

Adaptive Coordination Ant Colony Optimization for Multipoint Dynamic Aggregation

Will N. Browne, Bin Xin, G. Gao, 2021, IEEE Transactions on Cybernetics.

A Comparison of Learning Classifier Systems’ Rule Compaction Algorithms for Knowledge Visualization

Will N. Browne, Bing Xue, Yi Liu, 2021, ACM Trans. Evol. Learn. Optim..

Lévy-flight moth-flame optimisation algorithm-based micro-grid equipment sizing: An integrated investment and operational planning approach

Will N. Browne, A. Brent, Daniel Burmester, 2021 .

Design, implementation and testing of an intelligent knowledge-based system for the supervisory control of a hot rolling mill

Ian Postlethwaite, Will N. Browne, Da-Wei Gu, 2005 .

A Memetic Algorithm for the Task Allocation Problem on Multi-robot Multi-point Dynamic Aggregation Missions

Yi Mei, Will N. Browne, Bin Xin, 2020, 2020 IEEE Congress on Evolutionary Computation (CEC).

Particle swarm optimisation based AdaBoost for facial expression classification of still images

Mengjie Zhang, Will N. Browne, Will Browne, 2010, 2010 25th International Conference of Image and Vision Computing New Zealand.

In situ slip estimation for mobile robots in outdoor environments

Will N. Browne, Payam Nourizadeh, F. J. Stevens McFadden, 2022, J. Field Robotics.

Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection

Will N. Browne, Christopher F. Lehnert, Feras Dayoub, 2023, ArXiv.

An autonomous explore/exploit strategy

Will N. Browne, William N. L. Browne, Alex McMahon, 2005, GECCO '05.

Towards a developmental memory-based and embodied cognitive architecture

Will N. Browne, Paul E. Baxter, 2008 .

Producing Diverse Rashomon Sets of Counterfactual Explanations with Niching Particle Swarm Optimization Algorithms

Will N. Browne, Hayden Andersen, Andrew Lensen, 2023, GECCO.

Lateralized Learning for Multi-Class Visual Classification Tasks

Will N. Browne, Gina M. Grimshaw, G. Grimshaw, 2023, ArXiv.

Particle Swarm Optimisation for Feature Selection in Classification : A Multi-Objective Approach

Will N. Browne, Mengjie Zhang, Bing Xue, 2012 .

Evolutionary Feature Selection EC Paradigms Number of Objectives Single Objective Multi-Objective Evaluation Wrapper Approaches Filter Approaches Combined Approaches

Will N. Browne, Bing Xue, Mengjie Zhang, 2015 .

Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection

Will N. Browne, Christopher F. Lehnert, Feras Dayoub, 2023, IEEE Robotics and Automation Letters.

An abstraction agorithm for genetics-based reinforcement learning

Will N. Browne, William N. L. Browne, Dan Scott, 2005, GECCO '05.

Lateralization in Agents' Decision Making: Evidence of Benefits/Costs from Artificial Intelligence

Will N. Browne, Gina M. Grimshaw, G. Grimshaw, 2023, ArXiv.

Lateralized Learning to Solve Complex Boolean Problems

Will N. Browne, Gina M. Grimshaw, G. Grimshaw, 2022, IEEE Transactions on Cybernetics.

Prediction of moment-by-moment heart rate and skin conductance changes in the context of varying emotional arousal.

Will N. Browne, H. Eisenbarth, H. Shehu, 2023, Psychophysiology.

The Development of an Industrial Learning Classifier System for Data-Mining in a Steel Hop Strip Mill

Will N. Browne, Will N. Browne, 2004 .

Emotional arousal pattern (EMAP): A new database for modeling momentary subjective and psychophysiological responding to affective stimuli.

Will N. Browne, Bing Xue, H. Eisenbarth, 2023, Psychophysiology.

Cognitive Robotics

Will N. Browne, K. Kawamura, 2009, Encyclopedia of Complexity and Systems Science.

Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS

Will N. Browne, Jordan T. Bishop, M. Gallagher, 2022, GECCO.

ConCS: A Continual Classifier System for Continual Learning of Multiple Boolean Problems

Will N. Browne, Mengjie Zhang, T. Nguyen, 2023, IEEE Transactions on Evolutionary Computation.

Online Feature-Generation of Code Fragments for XCS to Guide Feature Construction

Mengjie Zhang, Will N. Browne, Will N. Browne, 2019, 2019 IEEE Congress on Evolutionary Computation (CEC).

Balancing Specificity and Generality in a Panmictic-Based Rule-Discovery Learning Classifier System

Will N. Browne, William N. L. Browne, 2002, IWLCS.

NEURAL NETWORK MODELS FOR THE PREDICTION OF ALUMINIUM HEATING AND ROLLING TIMES

I. Postlethwaite, Will N. Browne, T. Ozen, 2022 .

An Adversarial Attacks Resistance-based Approach to Emotion Recognition from Images using Facial Landmarks

Will N. Browne, Harisu Abdullahi Shehu, Will Browne, 2020, 2020 29th IEEE International Conference on Robot and Human Interactive Communication (RO-MAN).

A Comparison of Learning Classifier Systems’ Rule Compaction Algorithms for Knowledge Visualization

Will N. Browne, Bing Xue, Yi Liu, 2021, ACM Trans. Evol. Learn. Optim..

Modern Applications of Evolutionary Rule-based Machine Learning

Will N. Browne, Abubakar Siddique, R. Urbanowicz, 2023, GECCO Companion.

Three-cornered coevolution learning classifier systems for classification tasks

Will N. Browne, Mengjie Zhang, S. Marzukhi, 2014, GECCO.