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ORCIDJoshua D. Knowles
Person information
- affiliation: Schlumberger Cambridge Research Ltd., UK
- affiliation: University of Birmingham, UK
- affiliation (former): University of Manchester, School of Computer Science
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Books and Theses
- 2002
[b1]Joshua D. Knowles:
Local-search and hybrid evolutionary algorithms for Pareto optimization. University of Reading, UK, 2002
Journal Articles
- 2024
- [j25]Seyed Mahdi Shavarani
, Manuel López-Ibáñez, Joshua D. Knowles:
On Benchmarking Interactive Evolutionary Multiobjective Algorithms. IEEE Trans. Evol. Comput. 28(4): 1084-1098 (2024) - 2022
- [j24]Jamie Caldwell, Joshua D. Knowles, Christoph Thies, Filip Kubacki, Richard A. Watson:
Deep Optimisation: Transitioning the Scale of Evolutionary Search by Inducing and Searching in Deep Representations. SN Comput. Sci. 3(3): 253 (2022) - 2018
- [j23]Mario Garza-Fabre, Julia Handl, Joshua D. Knowles:
An Improved and More Scalable Evolutionary Approach to Multiobjective Clustering. IEEE Trans. Evol. Comput. 22(4): 515-535 (2018) - 2017
- [j22]Dimo Brockhoff, Joshua D. Knowles, Boris Naujoks, Karthik Sindhya:
Editorial. Comput. Oper. Res. 79: 264-265 (2017) - [j21]David L. Buckley, Ke Chen, Joshua D. Knowles:
Rapid Skill Capture in a First-Person Shooter. IEEE Trans. Comput. Intell. AI Games 9(1): 63-75 (2017) - 2016
- [j20]Mario Garza-Fabre, Shaun M. Kandathil, Julia Handl, Joshua D. Knowles, Simon C. Lovell:
Generating, Maintaining, and Exploiting Diversity in a Memetic Algorithm for Protein Structure Prediction. Evol. Comput. 24(4): 577-607 (2016) - 2015
- [j19]James Bradbury, Grégory Genta-Jouve, James William Allwood, Warwick B. Dunn, Royston Goodacre, Joshua D. Knowles, Shan He, Mark R. Viant:
MUSCLE: automated multi-objective evolutionary optimization of targeted LC-MS/MS analysis. Bioinform. 31(6): 975-977 (2015) - [j18]Richard Allmendinger, Julia Handl, Joshua D. Knowles:
Multiobjective optimization: When objectives exhibit non-uniform latencies. Eur. J. Oper. Res. 243(2): 497-513 (2015) - 2013
- [j17]Richard Allmendinger, Joshua D. Knowles:
On Handling Ephemeral Resource Constraints in Evolutionary Search. Evol. Comput. 21(3): 497-531 (2013) - [j16]Shaun M. Kandathil, Timothy L. Fletcher, Yongna Yuan, Joshua D. Knowles, Paul L. A. Popelier:
Accuracy and tractability of a kriging model of intramolecular polarizable multipolar electrostatics and its application to histidine. J. Comput. Chem. 34(21): 1850-1861 (2013) - 2010
- [j15]William Rowe, David C. Wedge, Mark Platt, Douglas B. Kell, Joshua D. Knowles:
Predictive models for population performance on real biological fitness landscapes. Bioinform. 26(17): 2145-2152 (2010) - [j14]Eric Bonabeau, David W. Corne, Joshua D. Knowles, Riccardo Poli:
Swarm intelligence theory: A snapshot of the state of the art. Theor. Comput. Sci. 411(21): 2081-2083 (2010) - 2009
- [j13]Julia Handl, Joshua D. Knowles, Simon C. Lovell:
Artefacts and biases affecting the evaluation of scoring functions on decoy sets for protein structure prediction. Bioinform. 25(10): 1271-1279 (2009) - [j12]Joshua D. Knowles:
Closed-loop evolutionary multiobjective optimization. IEEE Comput. Intell. Mag. 4(3): 77-91 (2009) - 2008
- [j11]Yisu Jin, Joshua D. Knowles, Hongmei Lu, Yizeng Liang, Douglas B. Kell:
The landscape adaptive particle swarm optimizer. Appl. Soft Comput. 8(1): 295-304 (2008) - 2007
- [j10]Julia Handl, Douglas B. Kell, Joshua D. Knowles:
Multiobjective Optimization in Bioinformatics and Computational Biology. IEEE ACM Trans. Comput. Biol. Bioinform. 4(2): 279-292 (2007) - [j9]Julia Handl, Joshua D. Knowles:
An Evolutionary Approach to Multiobjective Clustering. IEEE Trans. Evol. Comput. 11(1): 56-76 (2007) - 2006
- [j8]Julia Handl, Joshua D. Knowles, Marco Dorigo:
Ant-Based Clustering and Topographic Mapping. Artif. Life 12(1): 35-62 (2006) - [j7]Joshua D. Knowles:
ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems. IEEE Trans. Evol. Comput. 10(1): 50-66 (2006) - 2005
- [j6]Julia Handl, Joshua D. Knowles, Douglas B. Kell:
Computational cluster validation in post-genomic data analysis. Bioinform. 21(15): 3201-3212 (2005) - [j5]Leonora Bianchi, Joshua D. Knowles, Neill Bowler:
Local search for the probabilistic traveling salesman problem: Correction to the 2-p-opt and 1-shift algorithms. Eur. J. Oper. Res. 162(1): 206-219 (2005) - 2003
- [j4]Joshua D. Knowles, David Corne:
Properties of an adaptive archiving algorithm for storing nondominated vectors. IEEE Trans. Evol. Comput. 7(2): 100-116 (2003) - 2002
- [j3]Joshua D. Knowles, David W. Corne:
Enumeration of Pareto optimal multi-criteria spanning trees - a proof of the incorrectness of Zhou and Gen's proposed algorithm. Eur. J. Oper. Res. 143(3): 543-547 (2002) - 2000
- [j2]Joshua D. Knowles, David Corne:
Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy. Evol. Comput. 8(2): 149-172 (2000) - [j1]Joshua D. Knowles, David Corne:
A new evolutionary approach to the degree-constrained minimum spanning tree problem. IEEE Trans. Evol. Comput. 4(2): 125-134 (2000)
Conference and Workshop Papers
- 2024
- [c73]Benjamin Doerr, Joshua D. Knowles, Aneta Neumann, Frank Neumann:
A Block-Coordinate Descent EMO Algorithm: Theoretical and Empirical Analysis. GECCO 2024 - [c72]Stefan Pricopie, Richard Allmendinger, Manuel López-Ibáñez, Clyde Fare, Matt Benatan, Joshua D. Knowles:
Bayesian Optimization with Setup Switching Cost. GECCO Companion 2024: 103-104 - [c71]Joshua D. Knowles, Weijie Zheng:
Evolutionary Multiobjective Optimization (EMO). GECCO Companion 2024: 1432-1459 - [c70]Stefan Pricopie, Richard Allmendinger, Manuel López-Ibáñez, Clyde Fare, Matt Benatan, Joshua D. Knowles:
An Adaptive Approach to Bayesian Optimization with Setup Switching Costs. PPSN (2) 2024: 340-355 - 2023
- [c69]Seyed Mahdi Shavarani, Manuel López-Ibáñez, Richard Allmendinger, Joshua D. Knowles:
An Interactive Decision Tree-Based Evolutionary Multi-objective Algorithm. EMO 2023: 620-634 - 2022
- [c68]Stefan Pricopie, Richard Allmendinger, Manuel López-Ibáñez, Clyde Fare, Matt Benatan, Joshua D. Knowles:
Expensive optimization with production-graph resource constraints: a first look at a new problem class. GECCO 2022: 840-848 - [c67]Jake Atkinson, Richard Allmendinger, Joshua D. Knowles:
Inventing and Assessing Simple Heuristics for Bidding in Wholesale Electricity Markets. OR 2022: 245-251 - [c66]Chin Woei Lim, Richard Allmendinger, Joshua D. Knowles, Ayesha AlHosani, Mercedes Bleda:
Cooperative Multi-agent Search on Endogenously-Changing Fitness Landscapes. PPSN (1) 2022: 265-278 - 2021
- [c65]Jamie Caldwell, Joshua D. Knowles, Christoph Thies, Filip Kubacki, Richard A. Watson:
Deep Optimisation: Multi-scale Evolution by Inducing and Searching in Deep Representations. EvoApplications 2021: 506-521 - [c64]Seyed Mahdi Shavarani, Manuel López-Ibáñez, Joshua D. Knowles:
Realistic utility functions prove difficult for state-of-the-art interactive multiobjective optimization algorithms. GECCO 2021: 457-465 - 2017
- [c63]Mario Garza-Fabre, Julia Handl, Joshua D. Knowles:
A New Reduced-Length Genetic Representation for Evolutionary Multiobjective Clustering. EMO 2017: 236-251 - [c62]Jussi Hakanen, Joshua D. Knowles:
On Using Decision Maker Preferences with ParEGO. EMO 2017: 282-297 - [c61]Ofer M. Shir, Thomas Bäck, Joshua D. Knowles, Richard Allmendinger:
Sequential experimentation by evolutionary algorithms. GECCO (Companion) 2017: 828-851 - 2016
- [c60]Krzysztof Michalak, Joshua D. Knowles:
Simheuristics for the Multiobjective Nondeterministic Firefighter Problem in a Time-Constrained Setting. EvoApplications (2) 2016: 248-265 - [c59]Steve Miller, Joshua D. Knowles:
The Emergence of Cooperation in Public Goods Games on Randomly Growing Dynamic Networks. EvoApplications (1) 2016: 363-378 - [c58]Steve Miller, Joshua D. Knowles:
Global Network Cooperation Catalysed by a Small Prosocial Migrant Clique. UCNC 2016: 62-74 - 2015
- [c57]Steve Miller, Joshua D. Knowles:
A Minimal Model for the Emergence of Cooperation in Randomly Growing Networks. ECAL 2015: 114-121 - [c56]Andrew M. Webb, Julia Handl, Joshua D. Knowles:
How Much Should You Select for Evolvability? ECAL 2015: 487-494 - [c55]Manuel López-Ibáñez, Joshua D. Knowles:
Machine Decision Makers as a Laboratory for Interactive EMO. EMO (2) 2015: 295-309 - [c54]Mario Garza-Fabre, Shaun M. Kandathil, Julia Handl, Joshua D. Knowles, Simon C. Lovell:
Using Machine Learning to Explore the Relevance of Local and Global Features During Conformational Search in Rosetta. GECCO (Companion) 2015: 935-938 - 2014
- [c53]Andrew M. Webb, Joshua D. Knowles:
Studying the Evolvability of of Self-Encoding Genotype-Phenotype Maps. ALIFE 2014: 79-86 - [c52]Robert J. Lyon, J. M. Brooke, Joshua D. Knowles, Benjamin W. Stappers:
Hellinger Distance Trees for Imbalanced Streams. ICPR 2014: 1969-1974 - 2013
- [c51]Ahmad Almakhlafi, Joshua D. Knowles:
Systematic construction of algorithm portfolios for a Maintenance Scheduling Problem. IEEE Congress on Evolutionary Computation 2013: 245-252 - [c50]David L. Buckley, Ke Chen, Joshua D. Knowles:
Predicting skill from gameplay input to a first-person shooter. CIG 2013: 1-8 - [c49]Richard Allmendinger, Joshua D. Knowles:
'Hang On a Minute': Investigations on the Effects of Delayed Objective Functions in Multiobjective Optimization. EMO 2013: 6-20 - [c48]Julia Handl, Joshua D. Knowles:
Evidence Accumulation in Multiobjective Data Clustering. EMO 2013: 543-557 - [c47]Ricardo Aler, Julia Handl, Joshua D. Knowles:
Comparing multi-objective and threshold-moving ROC curve generation for a prototype-based classifier. GECCO 2013: 1029-1036 - [c46]Robert J. Lyon, J. M. Brooke, Joshua D. Knowles, Benjamin W. Stappers:
A Study on Classification in Imbalanced and Partially-Labelled Data Streams. SMC 2013: 1506-1511 - 2012
- [c45]Ahmad Almakhlafi, Joshua D. Knowles:
Benchmarks for maintenance scheduling problems in power generation. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c44]Julia Handl, Joshua D. Knowles:
Clustering Criteria in Multiobjective Data Clustering. PPSN (2) 2012: 32-41 - 2011
- [c43]Manuel López-Ibáñez, Joshua D. Knowles, Marco Laumanns:
On Sequential Online Archiving of Objective Vectors. EMO 2011: 46-60 - [c42]Richard Allmendinger, Joshua D. Knowles:
Policy learning in resource-constrained optimization. GECCO 2011: 1971-1978 - [c41]Richard Allmendinger, Joshua D. Knowles:
Evolutionary Search in Lethal Environments. IJCCI (ECTA-FCTA) 2011: 63-72 - 2010
- [c40]Thomas Bäck, Joshua D. Knowles, Ofer M. Shir:
Experimental optimization by evolutionary algorithms. GECCO (Companion) 2010: 2897-2916 - [c39]Richard Allmendinger, Joshua D. Knowles:
Evolutionary Optimization on Problems Subject to Changes of Variables. PPSN (2) 2010: 151-160 - [c38]Richard Allmendinger, Joshua D. Knowles:
On-Line Purchasing Strategies for an Evolutionary Algorithm Performing Resource-Constrained Optimization. PPSN (2) 2010: 161-170 - 2009
- [c37]Joshua D. Knowles, David Corne, Alan P. Reynolds:
Noisy Multiobjective Optimization on a Budget of 250 Evaluations. EMO 2009: 36-50 - 2008
- [c36]Caroline Farrelly, Douglas B. Kell, Joshua D. Knowles:
Molecular Structure Elucidation Using Ant Colony Optimization: A Preliminary Study. ANTS Conference 2008: 120-131 - [c35]Joshua D. Knowles, Hirotaka Nakayama:
Meta-Modeling in Multiobjective Optimization. Multiobjective Optimization 2008: 245-284 - [c34]Eckart Zitzler, Joshua D. Knowles, Lothar Thiele:
Quality Assessment of Pareto Set Approximations. Multiobjective Optimization 2008: 373-404 - [c33]Ludmil Mikhailov, Joshua D. Knowles:
Priority Elicitation in the AHP by a Pareto Envelope-Based Selection Algorithm. MCDM 2008: 249-257 - [c32]Julia Handl, Simon C. Lovell, Joshua D. Knowles:
Multiobjectivization by Decomposition of Scalar Cost Functions. PPSN 2008: 31-40 - [c31]Julia Handl, Simon C. Lovell, Joshua D. Knowles:
Investigations into the Effect of Multiobjectivization in Protein Structure Prediction. PPSN 2008: 702-711 - 2007
- [c30]Joshua D. Knowles, David Corne:
Quantifying the Effects of Objective Space Dimension in Evolutionary Multiobjective Optimization. EMO 2007: 757-771 - [c29]David W. Corne, Joshua D. Knowles:
Techniques for highly multiobjective optimisation: some nondominated points are better than others. GECCO 2007: 773-780 - 2006
- [c28]William Rowe, David Corne, Joshua D. Knowles:
Predicting Stochastic Search Algorithm Performance using Landscape State Machines. IEEE Congress on Evolutionary Computation 2006: 2944-2951 - [c27]Julia Handl, Joshua D. Knowles:
On semi-supervised clustering via multiobjective optimization. GECCO 2006: 1465-1472 - [c26]Julia Handl, Joshua D. Knowles:
Semi-supervised feature selection via multiobjective optimization. IJCNN 2006: 3319-3326 - [c25]Julia Handl, Joshua D. Knowles:
An Investigation of Representations and Operators for Evolutionary Data Clustering with a Variable Number of Clusters. PPSN 2006: 839-849 - 2005
- [c24]Julia Handl, Joshua D. Knowles:
Multiobjective clustering around medoids. Congress on Evolutionary Computation 2005: 632-639 - [c23]Julia Handl, Joshua D. Knowles:
Improvements to the scalability of multiobjective clustering. Congress on Evolutionary Computation 2005: 2372-2379 - [c22]Joshua D. Knowles, Evan J. Hughes:
Multiobjective Optimization on a Budget of 250 Evaluations. EMO 2005: 176-190 - [c21]Julia Handl, Joshua D. Knowles:
Exploiting the Trade-off - The Benefits of Multiple Objectives in Data Clustering. EMO 2005: 547-560 - [c20]Joshua D. Knowles:
A summary-attainment-surface plotting method for visualizing the performance of stochastic multiobjective optimizers. ISDA 2005: 552-557 - 2004
- [c19]Julia Handl, Joshua D. Knowles:
Evolutionary Multiobjective Clustering. PPSN 2004: 1081-1091 - 2003
- [c18]Julia Handl, Joshua D. Knowles, Marco Dorigo:
Strategies for the Increased Robustness of Ant-Based Clustering. Engineering Self-Organising Systems 2003: 90-104 - [c17]Joshua D. Knowles, David W. Corne, M. Fleischer:
Bounded archiving using the lebesgue measure. IEEE Congress on Evolutionary Computation 2003: 2490-2497 - [c16]David Corne, Joshua D. Knowles:
Some multiobjective optimizers are better than others. IEEE Congress on Evolutionary Computation 2003: 2506-2512 - [c15]Joshua D. Knowles, David Corne:
Instance Generators and Test Suites for the Multiobjective Quadratic Assignment Problem. EMO 2003: 295-310 - [c14]David Corne, Joshua D. Knowles:
No Free Lunch and Free Leftovers Theorems for Multiobjective Optimisation Problems. EMO 2003: 327-341 - [c13]Julia Handl, Joshua D. Knowles, Marco Dorigo:
On the Performance of Ant-based Clustering. HIS 2003: 204-213 - 2002
- [c12]Krzysztof Socha, Joshua D. Knowles, Michael Sampels:
A MAX-MIN Ant System for the University Course Timetabling Problem. Ant Algorithms 2002: 1-13 - [c11]Joshua D. Knowles, David Corne:
On metrics for comparing nondominated sets. IEEE Congress on Evolutionary Computation 2002: 711-716 - [c10]Joshua D. Knowles, David Corne:
Towards Landscape Analyses to Inform the Design of Hybrid Local Search for the Multiobjective Quadratic Assignment Problem. HIS 2002: 271-279 - [c9]Olivia Rossi-Doria, Michael Sampels, Mauro Birattari, Marco Chiarandini, Marco Dorigo, Luca Maria Gambardella, Joshua D. Knowles, Max Manfrin, Monaldo Mastrolilli, Ben Paechter, Luís Paquete, Thomas Stützle:
A Comparison of the Performance of Different Metaheuristics on the Timetabling Problem. PATAT 2002: 329-354 - [c8]Joshua D. Knowles, Richard A. Watson:
On the Utility of Redundant Encodings in Mutation-Based Evolutionary Search. PPSN 2002: 88-98 - 2001
- [c7]Joshua D. Knowles, David W. Corne:
A comparison of encodings and algorithms for multiobjective minimum spanning tree problems. CEC 2001: 544-551 - [c6]Joshua D. Knowles, Richard A. Watson, David Corne:
Reducing Local Optima in Single-Objective Problems by Multi-objectivization. EMO 2001: 269-283 - 2000
- [c5]Joshua D. Knowles, David W. Corne:
M-PAES: a memetic algorithm for multiobjective optimization. CEC 2000: 325-332 - [c4]Joshua D. Knowles, David Corne:
Heuristics for Evolutionary Off-line Routing in Telecommunication Networks. GECCO 2000: 574-581 - [c3]David Corne, Joshua D. Knowles, Martin J. Oates:
The Pareto Envelope-Based Selection Algorithm for Multi-objective Optimisation. PPSN 2000: 839-848 - [c2]Joshua D. Knowles, David Corne, Martin J. Oates:
On the Assessment of Multiobjective Approaches to the Adaptive Distributed Database Management Problem. PPSN 2000: 869-878 - 1999
- [c1]Joshua D. Knowles, David Corne:
The Pareto archived evolution strategy: a new baseline algorithm for Pareto multiobjective optimisation. CEC 1999: 98-105
Parts in Books or Collections
- 2023
- [p6]Richard Allmendinger, Joshua D. Knowles:
Heterogeneous Objectives: State-of-the-Art and Future Research. Many-Criteria Optimization and Decision Analysis 2023: 317-335 - 2012
- [p5]David W. Corne, Kalyanmoy Deb, Joshua D. Knowles, Xin Yao:
Selected Aspects of Natural Computing. Handbook of Natural Computing 2012: 1737-1801 - 2008
- [p4]Joshua D. Knowles, David Corne, Kalyanmoy Deb:
Introduction: Problem Solving, EC and EMO. Multiobjective Problem Solving from Nature 2008: 1-28 - [p3]Julia Handl, Joshua D. Knowles:
Modes of Problem Solving with Multiple Objectives: Implications for Interpreting the Pareto Set and for Decision Making. Multiobjective Problem Solving from Nature 2008: 131-151 - 2006
- [p2]Julia Handl, Joshua D. Knowles:
Multi-Objective Clustering and Cluster Validation. Multi-Objective Machine Learning 2006: 21-47 - 2004
- [p1]Joshua D. Knowles, David Corne:
Bounded Pareto Archiving: Theory and Practice. Metaheuristics for Multiobjective Optimisation 2004: 39-64
Editorship
- 2008
- [e1]Joshua D. Knowles, David Corne, Kalyanmoy Deb:
Multiobjective Problem Solving from Nature. Natural Computing Series, Springer 2008, ISBN 978-3-540-72963-1 [contents]
Reference Works
- 2017
- [r2]David W. Corne, Julia Handl, Joshua D. Knowles:
Evolutionary Clustering. Encyclopedia of Machine Learning and Data Mining 2017: 423-429 - 2010
- [r1]David Corne, Julia Handl, Joshua D. Knowles:
Evolutionary Clustering. Encyclopedia of Machine Learning 2010: 332-337
Informal and Other Publications
- 2024
- [i17]Benjamin Doerr, Joshua D. Knowles, Aneta Neumann, Frank Neumann:
A Block-Coordinate Descent EMO Algorithm: Theoretical and Empirical Analysis. CoRR abs/2404.03838 (2024) - [i16]Stefan Pricopie, Richard Allmendinger, Manuel López-Ibáñez, Clyde Fare, Matt Benatan, Joshua D. Knowles:
An adaptive approach to Bayesian Optimization with switching costs. CoRR abs/2405.08973 (2024) - 2022
- [i15]Chin Woei Lim, Richard Allmendinger, Joshua D. Knowles, Ayesha AlHosani, Mercedes Bleda:
Cooperative Multi-Agent Search on Endogenously-Changing Fitness Landscapes. CoRR abs/2206.13844 (2022) - 2021
- [i14]Richard Allmendinger, Joshua D. Knowles:
Heterogeneous Objectives: State-of-the-Art and Future Research. CoRR abs/2103.15546 (2021) - 2018
- [i13]J. R. Caldwell, Richard A. Watson, Christoph Thies, Joshua D. Knowles:
Deep Optimisation: Solving Combinatorial Optimisation Problems using Deep Neural Networks. CoRR abs/1811.00784 (2018) - [i12]Kathrin Klamroth, Joshua D. Knowles, Günter Rudolph, Margaret M. Wiecek:
Personalized Multiobjective Optimization: An Analytics Perspective (Dagstuhl Seminar 18031). Dagstuhl Reports 8(1): 33-99 (2018) - 2016
- [i11]Steve Miller, Joshua D. Knowles:
The Emergence of Cooperation in Public Goods Games on Randomly-Growing Dynamic Networks. CoRR abs/1603.05829 (2016) - [i10]Steve Miller, Joshua D. Knowles:
A minimal model for the emergence of cooperation in randomly growing networks. CoRR abs/1605.02651 (2016) - [i9]Steve Miller, Joshua D. Knowles:
Global network cooperation catalysed by a small prosocial migrant clique. CoRR abs/1605.02652 (2016) - 2015
- [i8]Salvatore Greco, Kathrin Klamroth, Joshua D. Knowles, Günter Rudolph:
Understanding Complexity in Multiobjective Optimization (Dagstuhl Seminar 15031). Dagstuhl Reports 5(1): 96-163 (2015) - 2014
- [i7]Robert J. Lyon, J. M. Brooke, Joshua D. Knowles, Benjamin W. Stappers:
Hellinger Distance Trees for Imbalanced Streams. CoRR abs/1405.2278 (2014) - [i6]Steve Miller, Joshua D. Knowles:
Population Fluctuation Promotes Cooperation in Networks. CoRR abs/1407.8032 (2014) - [i5]David L. Buckley, Ke Chen, Joshua D. Knowles:
Rapid Skill Capture in a First-Person Shooter. CoRR abs/1411.1316 (2014) - 2013
- [i4]Robert J. Lyon, J. M. Brooke, Joshua D. Knowles, Benjamin W. Stappers:
A Study on Classification in Imbalanced and Partially-Labelled Data Streams. CoRR abs/1307.8012 (2013) - 2012
- [i3]Salvatore Greco, Joshua D. Knowles, Kaisa Miettinen, Eckart Zitzler:
Learning in Multiobjective Optimization (Dagstuhl Seminar 12041). Dagstuhl Reports 2(1): 50-99 (2012) - 2009
- [i2]Jörg Fliege, Nicola Beume, Jürgen Branke, Heinrich Braun, Nirupam Chakraborti, Kalyanmoy Deb, Sabine Helwig, Joshua D. Knowles, Martin Middendorf, Sanaz Mostaghim, Silvia Poles, Daniel E. Salazar Aponte, Shukla Pradymn, El-Ghazali Talbi:
09041 Working Group on EMO for Robust Multiobjective Optimization (1st Round). Hybrid and Robust Approaches to Multiobjective Optimization 2009 - [i1]David W. Corne, Joshua D. Knowles:
Techniques for Highly Multiobjective Optimisation: Some Nondominated Points are Better than Others. CoRR abs/0908.3025 (2009)
Coauthor Index
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