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Will N. Browne

Will Neil Browne – Will N. L. Browne – William N. L. Browne

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Books and Theses

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2017
[b1]
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Ryan J. Urbanowicz, Will N. Browne:
Introduction to Learning Classifier Systems. Springer Briefs in Intelligent Systems, Springer 2017, ISBN 978-3-662-55006-9, pp. 1-123

Journal Articles

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2024
[j41]
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Payam Nourizadeh, Fiona J. Stevens McFadden, Will N. Browne:
In situ skid estimation for mobile robots in outdoor environments. J. Field Robotics 41(1): 179-194 (2024)
[j40]
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Harisu Abdullahi Shehu, Will N. Browne, Hedwig Eisenbarth:
Attention-Based Methods for Emotion Categorization From Partially Covered Faces. IEEE Trans. Emerg. Top. Comput. Intell. 8(1): 1057-1070 (2024)
2023
[j39]
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Payam Nourizadeh, Fiona Stevens McFadden, Will N. Browne:
In situ slip estimation for mobile robots in outdoor environments. J. Field Robotics 40(3): 467-482 (2023)
[j38]
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Nicolas Harvey Chapman, Feras Dayoub, Will N. Browne, Christopher F. Lehnert:
Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection. IEEE Robotics Autom. Lett. 8(8): 5084-5091 (2023)
[j37]
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Abubakar Siddique, Will N. Browne, Gina M. Grimshaw:
Lateralized Learning to Solve Complex Boolean Problems. IEEE Trans. Cybern. 53(11): 6761-6775 (2023)
[j36]
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Trung B. Nguyen, Will N. Browne, Mengjie Zhang:
ConCS: A Continual Classifier System for Continual Learning of Multiple Boolean Problems. IEEE Trans. Evol. Comput. 27(4): 1057-1071 (2023)
2022
[j35]
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Harisu Abdullahi Shehu, Will N. Browne, Hedwig Eisenbarth:
An anti-attack method for emotion categorization from images. Appl. Soft Comput. 128: 109456 (2022)
[j34]
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Harisu Abdullahi Shehu, Will N. Browne, Hedwig Eisenbarth:
A comparison of humans and machine learning classifiers categorizing emotion from faces with different coverings. Appl. Soft Comput. 130: 109701 (2022)
[j33]
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Yi Liu, Will N. Browne, Bing Xue:
Visualizations for rule-based machine learning. Nat. Comput. 21(2): 243-264 (2022)
[j32]
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Guanqiang Gao, Yi Mei, Ya-Hui Jia, Will N. Browne, Bin Xin:
Adaptive Coordination Ant Colony Optimization for Multipoint Dynamic Aggregation. IEEE Trans. Cybern. 52(8): 7362-7376 (2022)
[j31]
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Guanqiang Gao, Yi Mei, Bin Xin, Ya-Hui Jia, Will N. Browne:
Automated Coordination Strategy Design Using Genetic Programming for Dynamic Multipoint Dynamic Aggregation. IEEE Trans. Cybern. 52(12): 13521-13535 (2022)
[j30]
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Abubakar Siddique, Will N. Browne, Gina M. Grimshaw:
Frames-of-Reference-Based Learning: Overcoming Perceptual Aliasing in Multistep Decision-Making Tasks. IEEE Trans. Evol. Comput. 26(1): 174-187 (2022)
2021
[j29]
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Harisu Abdullahi Shehu, Will N. Browne, Hedwig Eisenbarth:
An Out-of-Distribution Attack Resistance Approach to Emotion Categorization. IEEE Trans. Artif. Intell. 2(6): 564-573 (2021)
[j28]
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Masaya Nakata, Will N. Browne:
Learning Optimality Theory for Accuracy-Based Learning Classifier Systems. IEEE Trans. Evol. Comput. 25(1): 61-74 (2021)
[j27]
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Yi Liu, Will N. Browne, Bing Xue:
A Comparison of Learning Classifier Systems' Rule Compaction Algorithms for Knowledge Visualization. ACM Trans. Evol. Learn. Optim. 1(3): 10:1-10:38 (2021)
2019
[j26]
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Arindam Bhakta, Christopher Hollitt, Will N. Browne, Marcus Frean:
Utility function generated saccade strategies for robot active vision: a probabilistic approach. Auton. Robots 43(4): 947-966 (2019)
[j25]
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
Figure-ground image segmentation using feature-based multi-objective genetic programming techniques. Neural Comput. Appl. 31(7): 3075-3094 (2019)
2017
[j24]
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Henry Williams, Will N. Browne, Dale A. Carnegie:
Learned Action SLAM: Sharing SLAM through learned path planning information between heterogeneous robotic platforms. Appl. Soft Comput. 50: 313-326 (2017)
[j23]
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
Genetic programming for evolving figure-ground segmentors from multiple features. Appl. Soft Comput. 51: 83-95 (2017)
[j22]
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
Image feature selection using genetic programming for figure-ground segmentation. Eng. Appl. Artif. Intell. 62: 96-108 (2017)
[j21]
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
Extending XCS with Cyclic Graphs for Scalability on Complex Boolean Problems. Evol. Comput. 25(2): 173-204 (2017)
2016
[j20]
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Syed Saud Naqvi, Will N. Browne, Christopher Hollitt:
Salient object detection via spectral matting. Pattern Recognit. 51: 209-224 (2016)
[j19]
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Muhammad Iqbal, Syed Saud Naqvi, Will N. Browne, Christopher Hollitt, Mengjie Zhang:
Learning feature fusion strategies for various image types to detect salient objects. Pattern Recognit. 60: 106-120 (2016)
[j18]
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Bing Xue, Mengjie Zhang, Will N. Browne, Xin Yao:
A Survey on Evolutionary Computation Approaches to Feature Selection. IEEE Trans. Evol. Comput. 20(4): 606-626 (2016)
[j17]
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Syed Saud Naqvi, Will N. Browne, Christopher Hollitt:
Feature Quality-Based Dynamic Feature Selection for Improving Salient Object Detection. IEEE Trans. Image Process. 25(9): 4298-4313 (2016)
2015
[j16]
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Syahaneim Marzukhi, Will N. Browne, Mengjie Zhang:
An on-line Pittsburgh LCS for the Three-Cornered Coevolution Framework. Evol. Intell. 8(4): 185-201 (2015)
[j15]
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Bing Xue, Mengjie Zhang, Will N. Browne:
A Comprehensive Comparison on Evolutionary Feature Selection Approaches to Classification. Int. J. Comput. Intell. Appl. 14(2): 1550008:1-1550008:23 (2015)
[j14]
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
Improving genetic search in XCS-based classifier systems through understanding the evolvability of classifier rules. Soft Comput. 19(7): 1863-1880 (2015)
2014
[j13]
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Bing Xue, Mengjie Zhang, Will N. Browne:
Particle swarm optimisation for feature selection in classification: Novel initialisation and updating mechanisms. Appl. Soft Comput. 18: 261-276 (2014)
[j12]
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Toktam Ebadi, Ignas Kukenys, Will N. Browne, Mengjie Zhang:
Human-Interpretable Feature Pattern Classification System Using Learning Classifier Systems. Evol. Comput. 22(4): 629-650 (2014)
[j11]
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Bing Xue, Liam Cervante, Lin Shang, Will N. Browne, Mengjie Zhang:
Binary PSO and Rough Set Theory for Feature Selection: a Multi-objective filter Based Approach. Int. J. Comput. Intell. Appl. 13(2) (2014)
[j10]
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
Reusing Building Blocks of Extracted Knowledge to Solve Complex, Large-Scale Boolean Problems. IEEE Trans. Evol. Comput. 18(4): 465-480 (2014)
2013
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
Learning complex, overlapping and niche imbalance Boolean problems using XCS-based classifier systems. Evol. Intell. 6(2): 73-91 (2013)
[j8]
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Syahaneim Marzukhi, Will N. Browne, Mengjie Zhang:
Adaptive artificial datasets through learning classifier systems for classification tasks. Evol. Intell. 6(2): 93-107 (2013)
[j7]
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Bing Xue, Liam Cervante, Lin Shang, Will N. Browne, Mengjie Zhang:
Multi-objective Evolutionary Algorithms for filter Based Feature Selection in Classification. Int. J. Artif. Intell. Tools 22(4) (2013)
[j6]
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
Evolving optimum populations with XCS classifier systems - XCS with code fragmented action. Soft Comput. 17(3): 503-518 (2013)
[j5]
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Bing Xue, Mengjie Zhang, Will N. Browne:
Particle Swarm Optimization for Feature Selection in Classification: A Multi-Objective Approach. IEEE Trans. Cybern. 43(6): 1656-1671 (2013)
2012
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Bing Xue, Liam Cervante, Lin Shang, Will N. Browne, Mengjie Zhang:
A multi-objective particle swarm optimisation for filter-based feature selection in classification problems. Connect. Sci. 24(2-3): 91-116 (2012)
2010
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Richard J. Mitchell, Kevin Warwick, Will N. Browne, Mark Gasson, Jim Wyatt:
Engaging Robots: Innovative Outreach for Attracting Cybernetics Students. IEEE Trans. Educ. 53(1): 105-113 (2010)
2008
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Jim Wyatt, Will N. Browne, Mark Gasson, Kevin Warwick:
Consumer Robotic Products. IEEE Robotics Autom. Mag. 15(1): 71-79 (2008)
2006
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Will N. Browne, L. Yao, Ian Postlethwaite, S. Lowes, M. Mar:
Knowledge-elicitation and data-mining: Fusing human and industrial plant information. Eng. Appl. Artif. Intell. 19(3): 345-359 (2006)

Conference and Workshop Papers

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2024
[c114]
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  - conf/gecco/AndersenLB024
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Hayden Andersen, Andrew Lensen, Will N. Browne, Yi Mei:
Intepretable Local Explanations Through Genetic Programming. GECCO Companion 2024: 247-250
[c113]
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Yi Liu, Yu Cui, Wen Cheng, Will Neil Browne, Bing Xue, Chengyuan Zhu, Yiding Zhang, Mingkai Sheng, Lingfang Zeng:
A Phenotypic Learning Classifier System for Problems with Continuous Features. GECCO 2024
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Fumito Uwano, Will Neil Browne:
Cognitive Learning System for Sequential Aliasing Patterns of States in Multistep Decision-Making. GECCO Companion 2024: 315-318
[c111]
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Abubakar Siddique, Will N. Browne, Ryan J. Urbanowicz:
Evolutionary Machine Learning for Interpretable and eXplainable AI. GECCO Companion 2024: 1038-1068
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Cameron Coombe, David Howard, Will N. Browne:
Learning Classifier Systems as a Solver for the Abstraction and Reasoning Corpus. GECCO Companion 2024: 1770-1778
2023
[c109]
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Yi Liu, Yu Cui, Will N. Browne, Bing Xue, Wen Cheng, Yong Li, Lingfang Zeng:
Absumption and Subsumption based Learning Classifier System for Real-World Continuous-based Problems. GECCO Companion 2023: 299-302
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Abubakar Siddique, Muhammad Iqbal, Shahab Din, Will N. Browne:
Attention in Rule-Based Machine Learning: Exploiting Learning Classifier Systems' Generalization for Image Classification. GECCO Companion 2023: 323-326
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Fumito Uwano, Will N. Browne:
Hierarchical Frames-of-References in Learning Classifier Systems. GECCO Companion 2023: 335-338
[c106]
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Hayden Andersen, Andrew Lensen, Will N. Browne, Yi Mei:
Producing Diverse Rashomon Sets of Counterfactual Explanations with Niching Particle Swarm Optimization Algorithms. GECCO 2023: 393-401
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Abubakar Siddique, Will N. Browne, Ryan J. Urbanowicz:
Modern Applications of Evolutionary Rule-based Machine Learning. GECCO Companion 2023: 1301-1330
2022
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Hayden Andersen, Andrew Lensen, Will N. Browne, Yi Mei:
Evolving Counterfactual Explanations with Particle Swarm Optimization and Differential Evolution. CEC 2022: 1-8
[c103]
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Yi Liu, Will N. Browne, Bing Xue:
A comparison of rule compaction algorithms for michigan style learning classifier systems. GECCO Companion 2022: 31-32
[c102]
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  - conf/gecco/BishopGB22
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Jordan T. Bishop, Marcus Gallagher, Will N. Browne:
Pittsburgh learning classifier systems for explainable reinforcement learning: comparing with XCS. GECCO 2022: 323-331
[c101]
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Abubakar Siddique, Will N. Browne:
Learning classifier systems: cognitive inspired machine learning for eXplainable AI. GECCO Companion 2022: 1081-1110
[c100]
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Hayden Andersen, Andrew Lensen, Will N. Browne:
Improving the search of learning classifier systems through interpretable feature clustering. GECCO Companion 2022: 1752-1756
2021
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Trung B. Nguyen, Will N. Browne, Mengjie Zhang:
Constructing Complexity-efficient Features in XCS with Tree-based Rule Conditions. CEC 2021: 296-303
[c98]
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Harisu Abdullahi Shehu, Will N. Browne, Hedwig Eisenbarth:
Particle Swarm Optimization for Feature Selection in Emotion Categorization. CEC 2021: 752-759
[c97]
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Harisu Abdullahi Shehu, Abubakar Siddique, Will N. Browne, Hedwig Eisenbarth:
Lateralized Approach for Robustness Against Attacks in Emotion Categorization from Images. EvoApplications 2021: 469-485
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Will N. Browne:
Advanced Learning Classifier Systems. GECCO Companion 2021: 669-691
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Jordan T. Bishop, Marcus Gallagher, Will N. Browne:
A genetic fuzzy system for interpretable and parsimonious reinforcement learning policies. GECCO Companion 2021: 1630-1638
[c94]
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Soheil Mohseni, Alan C. Brent, Daniel Burmester, Will N. Browne, Scott Kelly:
Adding a Computationally-Tractable Probabilistic Dimension to Meta-Heuristic-Based Microgrid Sizing. TENCON 2021: 464-469
2020
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Guanqiang Gao, Yi Mei, Bin Xin, Ya-Hui Jia, Will N. Browne:
A Memetic Algorithm for the Task Allocation Problem on Multi-robot Multi-point Dynamic Aggregation Missions. CEC 2020: 1-8
[c92]
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Yi Liu, Will N. Browne, Bing Xue:
Absumption and subsumption based learning classifier systems. GECCO 2020: 368-376
[c91]
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Trung B. Nguyen, Will N. Browne, Mengjie Zhang:
Relatedness measures to aid the transfer of building blocks among multiple tasks. GECCO 2020: 377-385
[c90]
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Abubakar Siddique, Will N. Browne, Gina M. Grimshaw:
Lateralized learning for robustness against adversarial attacks in a visual classification system. GECCO 2020: 395-403
[c89]
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Abubakar Siddique, Will N. Browne, Gina M. Grimshaw:
Learning classifier systems: appreciating the lateralized approach. GECCO Companion 2020: 1807-1815
[c88]
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Harisu Abdullahi Shehu, Will N. Browne, Hedwig Eisenbarth:
Emotion Categorization from Video-Frame Images Using a Novel Sequential Voting Technique. ISVC (2) 2020: 618-632
[c87]
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Harisu Abdullahi Shehu, Will N. Browne, Hedwig Eisenbarth:
An Adversarial Attacks Resistance-based Approach to Emotion Recognition from Images using Facial Landmarks. RO-MAN 2020: 1307-1314
2019
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Zheming Zhang, Will N. Browne, Dale A. Carnegie:
XCS with Combined Reward Method (XCSCR) for Policy Search in Multistep Problems. CEC 2019: 2982-2989
[c85]
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Trung B. Nguyen, Will N. Browne, Mengjie Zhang:
Online Feature-Generation of Code Fragments for XCS to Guide Feature Construction. CEC 2019: 3308-3315
[c84]
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Masaya Nakata, Will Neil Browne:
How XCS can prevent misdistinguishing rule accuracy: a preliminary study. GECCO (Companion) 2019: 183-184
[c83]
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Yi Liu, Will N. Browne, Bing Xue:
Absumption to complement subsumption in learning classifier systems. GECCO 2019: 410-418
[c82]
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Trung B. Nguyen, Will N. Browne, Mengjie Zhang:
Improvement of code fragment fitness to guide feature construction in XCS. GECCO 2019: 428-436
[c81]
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Megan Liang, Gabrielle Palado, Will N. Browne:
Identifying Simple Shapes to Classify the Big Picture. IVCNZ 2019: 1-6
2018
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Yi Liu, Will N. Browne, Bing Xue:
Hierarchical Learning Classifier Systems for Polymorphism in Heterogeneous Niches. Australasian Conference on Artificial Intelligence 2018: 397-409
[c79]
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Xiu Cheng, Will N. Browne, Mengjie Zhang:
Decomposition Based Multi-Objective Evolutionary Algorithm in XCS for Multi-Objective Reinforcement Learning. CEC 2018: 1-8
[c78]
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Yi Liu, Will N. Browne, Bing Xue:
Adapting Bagging and Boosting to Learning Classifier Systems. EvoApplications 2018: 405-420
[c77]
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Masaya Nakata, Will N. Browne, Tomoki Hamagami:
Theoretical adaptation of multiple rule-generation in XCS. GECCO 2018: 482-489
[c76]
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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, Per Kristian Lehre, Xiaodong Li, Andrei Lissovoi, Pekka Malo, Luis Martí, Yi Mei, Juan Julián Merelo Guervós, Julian F. Miller, Alberto Moraglio, Antonio J. Nebro, Su Nguyen, Gabriela Ochoa, Pietro S. Oliveto, Stjepan Picek, Nelishia Pillay, Mike Preuss, Marc Schoenauer, Roman Senkerik, Ankur Sinha, Ofer M. Shir, Dirk Sudholt, L. Darrell Whitley, Mark Wineberg, John R. Woodward, Mengjie Zhang:
Tutorials at PPSN 2018. PPSN (2) 2018: 477-489
2017
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
Wrapper Feature Construction for Figure-Ground Image Segmentation Using Genetic Programming. ACALCI 2017: 111-123
[c74]
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  - conf/caad-futures/CichockaMBR17
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Judyta M. Cichocka, Agata Migalska, Will N. Browne, Edgar Rodriguez:
SILVEREYE - The Implementation of Particle Swarm Optimization Algorithm in a Design Optimization Tool. CAAD Futures 2017: 151-169
[c73]
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
Learning figure-ground image segmentors by genetic programming. GECCO (Companion) 2017: 239-240
[c72]
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Masaya Nakata, Will N. Browne, Tomoki Hamagami, Keiki Takadama:
Theoretical XCS parameter settings of learning accurate classifiers. GECCO 2017: 473-480
[c71]
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Yi Liu, Bing Xue, Will N. Browne:
Visualisation and Optimisation of Learning Classifier Systems for Multiple Domain Learning. SEAL 2017: 448-461
2016
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Isidro M. Alvarez, Will N. Browne, Mengjie Zhang:
Compaction for Code Fragment Based Learning Classifier Systems. ACALCI 2016: 41-53
[c69]
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
Multi-objective Genetic Programming for Figure-Ground Image Segmentation. ACALCI 2016: 134-146
[c68]
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Yi Liu, Muhammad Iqbal, Isidro M. Alvarez, Will N. Browne:
Integration of code-fragment based learning classifier systems for multiple domain perception and learning. CEC 2016: 2177-2184
[c67]
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Abubakar Siddique, Muhammad Iqbal, Will N. Browne:
A comprehensive strategy for mammogram image classification using learning classifier systems. CEC 2016: 2201-2208
[c66]
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Syed Saud Naqvi, Will N. Browne:
Adapting learning classifier systems to symbolic regression. CEC 2016: 2209-2216
[c65]
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Isidro M. Alvarez, Will N. Browne, Mengjie Zhang:
Compaction for code fragment based learning classifier systems - Redux. CEC 2016: 2217-2224
[c64]
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
Figure-ground image segmentation using genetic programming and feature selection. CEC 2016: 3839-3846
[c63]
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Isidro M. Alvarez, Will N. Browne, Mengjie Zhang:
Human-inspired Scaling in Learning Classifier Systems: Case Study on the n-bit Multiplexer Problem Set. GECCO 2016: 429-436
[c62]
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Will N. Browne:
Code Fragments: Past and Future use in Transfer Learning. GECCO (Companion) 2016: 1405
[c61]
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Ryan J. Urbanowicz, Will N. Browne, Karthik Kuber:
Hands-on Workshop on Learning Classifier Systems. GECCO (Companion) 2016: 1407-1408
[c60]
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
Proceedings in Adaptation, Learning and Optimization. IES 2016: 237-250
2015
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Henry Williams, Christopher P. Lee-Johnson, Will N. Browne, Dale A. Carnegie:
Emotion inspired adaptive robotic path planning. CEC 2015: 3004-3011
[c58]
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Masaya Nakata, Pier Luca Lanzi, Tim Kovacs, Will Neil Browne, Keiki Takadama:
How should Learning Classifier Systems cover a state-action space? CEC 2015: 3012-3019
[c57]
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
A Supervised Figure-Ground Segmentation Method Using Genetic Programming. EvoApplications 2015: 491-503
[c56]
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Ryan J. Urbanowicz, Will N. Browne:
Introducing Rule-based Machine Learning: A Practical Guide. GECCO (Companion) 2015: 263-292
[c55]
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Will N. Browne:
Back to the Future: Learning Classifier Systems as Cognitive Systems. GECCO (Companion) 2015: 1037
[c54]
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A. Roberts, Will N. Browne, Christopher Hollitt:
Accurate marker based distance measurement with single camera. IVCNZ 2015: 1-6
[c53]
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Henry Williams, Syed Saud Naqvi, Will N. Browne, Christopher Hollitt:
Introduction of a human based attention model for robotic navigation. IVCNZ 2015: 1-6
2014
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Syed Saud Naqvi, Will N. Browne, Christopher Hollitt:
Genetic algorithms based feature combination for salient object detection, for autonomously identified image domain types. IEEE Congress on Evolutionary Computation 2014: 109-116
[c51]
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  - conf/educon/CarnegieB14
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Dale A. Carnegie, Will N. Browne:
Factors that affect the design of a successful engineering programme: A case study. EDUCON 2014: 62-68
[c50]
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Muhammad Iqbal, Syed Saud Naqvi, Will N. Browne, Christopher Hollitt, Mengjie Zhang:
Salient object detection using learning classifiersystems that compute action mappings. GECCO 2014: 525-532
[c49]
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Syahaneim Marzukhi, Will N. Browne, Mengjie Zhang:
Three-cornered coevolution learning classifier systems for classification tasks. GECCO 2014: 549-556
[c48]
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Isidro M. Alvarez, Will N. Browne, Mengjie Zhang:
Reusing learned functionality in XCS: code fragments with constructed functionality and constructed features. GECCO (Companion) 2014: 969-976
[c47]
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Isidro M. Alvarez, Will N. Browne, Mengjie Zhang:
Reusing Learned Functionality to Address Complex Boolean Functions. SEAL 2014: 383-394
[c46]
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Syed Saud Naqvi, Will N. Browne, Christopher Hollitt:
Evolutionary Feature Combination Based Seed Learning for Diffusion-Based Saliency. SEAL 2014: 822-834
[c45]
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Yuyu Liang, Mengjie Zhang, Will N. Browne:
Image Segmentation: A Survey of Methods Based on Evolutionary Computation. SEAL 2014: 847-859
2013
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Roman Klapaukh, Will N. Browne, Mengjie Zhang:
The effect of primitive sets on the expression of evolved images. IEEE Congress on Evolutionary Computation 2013: 725-732
[c43]
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Syed Saud Naqvi, Will N. Browne, Christopher Hollitt:
Optimizing visual attention models for predicting human fixations using Genetic Algorithms. IEEE Congress on Evolutionary Computation 2013: 1302-1309
[c42]
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
Learning overlapping natured and niche imbalance boolean problems using XCS classifier systems. IEEE Congress on Evolutionary Computation 2013: 1818-1825
[c41]
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Aaron Scoble, Will N. Browne, Bill Stephenson, Zane Bruce, Mengjie Zhang:
Evolutionary spatial auto-correlation for assessing earthquake liquefaction potential using Parallel Linear Genetic Programming. IEEE Congress on Evolutionary Computation 2013: 2940-2947
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Bing Xue, Mengjie Zhang, Will N. Browne:
Novel Initialisation and Updating Mechanisms in PSO for Feature Selection in Classification. EvoApplications 2013: 428-438
[c39]
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Bing Xue, Mengjie Zhang, Yan Dai, Will N. Browne:
PSO for feature construction and binary classification. GECCO 2013: 137-144
[c38]
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Syahaneim Marzukhi, Will N. Browne, Mengjie Zhang:
Adaptive artificial datasets to discover the effects of domain features for classification tasks. GECCO (Companion) 2013: 157-158
[c37]
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Will N. Browne, Ryan J. Urbanowicz:
Learning classifier systems: introducing the user-friendly textbook. GECCO (Companion) 2013: 439-468
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
Extending learning classifier system with cyclic graphs for scalability on complex, large-scale boolean problems. GECCO 2013: 1045-1052
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
Comparison of two methods for computing action values in XCS with code-fragment actions. GECCO (Companion) 2013: 1235-1242
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Syahaneim Marzukhi, Will N. Browne, Mengjie Zhang:
Adaptive artificial datasets through learning classifier systems for classification tasks. GECCO (Companion) 2013: 1243-1250
[c33]
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Arindam Bhakta, Marcus Frean, Christopher Hollitt, Will N. Browne:
Trading off salience and uncertainty in sampling a visual scene. IVCNZ 2013: 236-241
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Syed Saud Naqvi, Will N. Browne, Christopher Hollitt:
Combining object-based local and global feature statistics for salient object search. IVCNZ 2013: 394-399
2012
[c31]
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Bing Xue, Mengjie Zhang, Will N. Browne:
Single Feature Ranking and Binary Particle Swarm Optimisation Based Feature Subset Ranking for Feature Selection. ACSC 2012: 27-36
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
XCSR with Computed Continuous Action. Australasian Conference on Artificial Intelligence 2012: 350-361
[c29]
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Henry Williams, Will N. Browne:
Integration of Learning Classifier Systems with simultaneous localisation and mapping for autonomous robotics. IEEE Congress on Evolutionary Computation 2012: 1-8
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Bing Xue, Mengjie Zhang, Will N. Browne:
New fitness functions in binary particle swarm optimisation for feature selection. IEEE Congress on Evolutionary Computation 2012: 1-8
[c27]
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Dale A. Carnegie, Craig A. Watterson, Peter Andreae, Will N. Browne:
Prediction of success in engineering study. EDUCON 2012: 1-9
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Dale A. Carnegie, Craig A. Watterson, Will N. Browne, James MacKay, Mel Lock, John Williams, Michael Forret:
Strategies to improve engineering retention. EDUCON 2012: 1-10
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Bing Xue, Mengjie Zhang, Will N. Browne:
Multi-objective particle swarm optimisation (PSO) for feature selection. GECCO 2012: 81-88
[c24]
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Toktam Ebadi, Mengjie Zhang, Will N. Browne:
XCS-based versus UCS-based feature pattern classification system. GECCO 2012: 839-846
[c23]
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Muhammad Iqbal, Will N. Browne, Mengjie Zhang:
Extracting and using building blocks of knowledge in learning classifier systems. GECCO 2012: 863-870
[c22]
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Syahaneim Marzukhi, Will N. Browne, Mengjie Zhang:
Two-cornered learning classifier systems for pattern generation and classification. GECCO 2012: 895-902
2011
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Ignas Kukenys, Will N. Browne, Mengjie Zhang:
Transparent, Online Image Pattern Classification Using a Learning Classifier System. EvoApplications (1) 2011: 183-193
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Ignas Kukenys, Will N. Browne, Mengjie Zhang:
Confusion matrices for improving performance of feature pattern classifier systems. GECCO (Companion) 2011: 181-182
[c19]
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Muhammad Iqbal, Mengjie Zhang, Will N. Browne:
Automatically defined functions for learning classifier systems. GECCO (Companion) 2011: 375-382
[c18]
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Syahaneim Marzukhi, Will N. Browne, Mengjie Zhang:
Developing an evolvable pattern generator using learning classifier systems. ICARA 2011: 163-168
2010
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Rachel Hunt, Mark Johnston, Will N. Browne, Mengjie Zhang:
Sampling Methods in Genetic Programming for Classification with Unbalanced Data. Australasian Conference on Artificial Intelligence 2010: 273-282
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Daniel L. Atkins, Roman Klapaukh, Will N. Browne, Mengjie Zhang:
Evolution of aesthetically pleasing images without human-in-the-loop. IEEE Congress on Evolutionary Computation 2010: 1-8
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Jan Larres, Mengjie Zhang, Will N. Browne:
Using unrestricted loops in genetic programming for image classification. IEEE Congress on Evolutionary Computation 2010: 1-8
[c14]
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Paul Baxter, Will N. Browne:
Memory as the Substrate of Cognition: A Developmental Cognitive Robotics Perspective. EpiRob 2010
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Ammar W. Mohemmed, Mengjie Zhang, Will N. Browne:
Particle swarm optimisation for outlier detection. GECCO 2010: 83-84
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Carlton Downey, Mengjie Zhang, Will N. Browne:
New crossover operators in linear genetic programming for multiclass object classification. GECCO 2010: 885-892
2009
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  - conf/ecal/BaxterB09
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Paul Baxter, Will N. Browne:
Memory-Based Cognitive Framework: A Low-Level Association Approach to Cognitive Architectures. ECAL (1) 2009: 402-409
[c10]
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  - conf/gecco/Davis-MoradkhanBG09
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Madeleine Davis-Moradkhan, Will N. Browne, Peter Grindrod:
Extending evolutionary algorithms to discover tri-criterion and non-supported solutions for the minimum spanning tree problem. GECCO 2009: 1829-1830
2008
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Madeleine Davis-Moradkhan, Will N. Browne:
A Hybridised Evolutionary Algorithm for Multi-Criterion Minimum Spanning Tree Problems. HIS 2008: 290-295
2007
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Will N. Browne, Charalambos Ioannides:
Investigating scaling of an abstracted LCS utilising ternary and s-expression alphabets. GECCO (Companion) 2007: 2759-2764
[c7]
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Charalambos Ioannides, Will N. Browne:
Investigating Scaling of an Abstracted LCS Utilising Ternary and S-Expression Alphabets. IWLCS 2007: 46-56
2006
[c6]
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Madeleine Davis-Moradkhan, Will N. Browne:
A Knowledge-Based Evolution Strategy for the Multi-Objective Minimum Spanning Tree Problem. IEEE Congress on Evolutionary Computation 2006: 1391-1398
[c5]
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Philip T. Elliott, Diven Topiwala, Will N. Browne:
Training Reformulated Product Units in Hybrid Neural Networks. IJCNN 2006: 5051-5058
2005
[c4]
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  - conf/gecco/McMahonSB05
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Alex McMahon, Dan Scott, William N. L. Browne:
An autonomous explore/exploit strategy. GECCO Workshops 2005: 103-108
[c3]
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William N. L. Browne, Dan Scott:
An abstraction agorithm for genetics-based reinforcement learning. GECCO 2005: 1875-1882
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F. C. Gee, Will N. Browne, Kazuhiko Kawamura:
Uncanny valley revisited. RO-MAN 2005: 151-157
2002
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William N. L. Browne:
Balancing Specificity and Generality in a Panmictic-Based Rule-Discovery Learning Classifier System. IWLCS 2002: 1-19

Parts in Books or Collections

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2008
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Bernhard Anrig, Will N. Browne, Mark Gasson:
The Role of Algorithms in Profiling. Profiling the European Citizen 2008: 65-87
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William N. L. Browne:
Improving Evolutionary Computation Based Data-Mining for the Process Industry: The Importance of Abstraction. Learning Classifier Systems in Data Mining 2008: 47-68

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2014
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Grant Dick, Will N. Browne, Peter A. Whigham, Mengjie Zhang, Lam Thu Bui, Hisao Ishibuchi, Yaochu Jin, Xiaodong Li, Yuhui Shi, Pramod Singh, Kay Chen Tan, Ke Tang:
Simulated Evolution and Learning - 10th International Conference, SEAL 2014, Dunedin, New Zealand, December 15-18, 2014. Proceedings. Lecture Notes in Computer Science 8886, Springer 2014, ISBN 978-3-319-13562-5 [contents]
2010
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Jaume Bacardit, Will N. Browne, Jan Drugowitsch, Ester Bernadó-Mansilla, Martin V. Butz:
Learning Classifier Systems - 11th International Workshop, IWLCS 2008, Atlanta, GA, USA, July 13, 2008, and 12th International Workshop, IWLCS 2009, Montreal, QC, Canada, July 9, 2009, Revised Selected Papers. Lecture Notes in Computer Science 6471, Springer 2010, ISBN 978-3-642-17507-7 [contents]

Reference Works

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2009
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Kazuhiko Kawamura, Will N. Browne:
Cognitive Robotics. Encyclopedia of Complexity and Systems Science 2009: 1109-1126

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2024
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Nicolas Harvey Chapman, Feras Dayoub, Will N. Browne, Chris Lehnert:
Enhancing Embodied Object Detection through Language-Image Pre-training and Implicit Object Memory. CoRR abs/2402.03721 (2024)
[i10]
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Tjeard van Oort, Dimity Miller, Will N. Browne, Nicolas Marticorena, Jesse Haviland, Niko Sünderhauf:
Open-Vocabulary Part-Based Grasping. CoRR abs/2406.05951 (2024)
2023
[i9]
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Abubakar Siddique, Will N. Browne, Gina M. Grimshaw:
Lateralized Learning for Multi-Class Visual Classification Tasks. CoRR abs/2301.12637 (2023)
[i8]
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Abubakar Siddique, Will N. Browne, Gina M. Grimshaw:
Lateralization in Agents' Decision Making: Evidence of Benefits/Costs from Artificial Intelligence. CoRR abs/2302.01542 (2023)
[i7]
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Nicolas Harvey Chapman, Feras Dayoub, Will N. Browne, Christopher F. Lehnert:
Predicting Class Distribution Shift for Reliable Domain Adaptive Object Detection. CoRR abs/2302.06039 (2023)
[i6]
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Jordan T. Bishop, Marcus Gallagher, Will N. Browne:
A Genetic Fuzzy System for Interpretable and Parsimonious Reinforcement Learning Policies. CoRR abs/2305.09922 (2023)
[i5]
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Jordan T. Bishop, Marcus Gallagher, Will N. Browne:
Pittsburgh Learning Classifier Systems for Explainable Reinforcement Learning: Comparing with XCS. CoRR abs/2305.09945 (2023)
[i4]
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Payam Nourizadeh, Fiona J. Stevens McFadden, Will N. Browne:
Trajectory Tracking Control of Skid-Steering Mobile Robots with Slip and Skid Compensation using Sliding-Mode Control and Deep Learning. CoRR abs/2309.08863 (2023)
2020
[i3]
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  - journals/corr/abs-2004-10978
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Trung B. Nguyen, Will N. Browne, Mengjie Zhang:
Constructing Complexity-efficient Features in XCS with Tree-based Rule Conditions. CoRR abs/2004.10978 (2020)
[i2]
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Trung B. Nguyen, Will N. Browne, Mengjie Zhang:
Relatedness Measures to Aid the Transfer of Building Blocks among Multiple Tasks. CoRR abs/2005.03947 (2020)
[i1]
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Isidro M. Alvarez, Trung B. Nguyen, Will N. Browne, Mengjie Zhang:
A Layered Learning Approach to Scaling in Learning Classifier Systems for Boolean Problems. CoRR abs/2006.01415 (2020)

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