Joshua D. Knowles

发表

Population Fluctuation Promotes Cooperation in Networks

Steve Miller, Joshua D. Knowles, 2015, Scientific reports.

On Handling Ephemeral Resource Constraints in Evolutionary Search

Joshua D. Knowles, Richard Allmendinger, 2013, Evolutionary Computation.

A New Reduced-Length Genetic Representation for Evolutionary Multiobjective Clustering

Joshua D. Knowles, Mario Garza-Fabre, Julia Handl, 2017, EMO.

Sequential experimentation by evolutionary algorithms

Ofer M. Shir, Thomas Bäck, Joshua D. Knowles, 2017, GECCO.

Exploiting the Trade-off - The Benefits of Multiple Objectives in Data Clustering

Joshua D. Knowles, Julia Handl, 2005, EMO.

Meta-Modeling in Multiobjective Optimization

Hirotaka Nakayama, Joshua D. Knowles, 2008, Multiobjective Optimization.

A MAX-MIN Ant System for the University Course Timetabling Problem

Michael Sampels, Joshua D. Knowles, Krzysztof Socha, 2002, Ant Algorithms.

Predicting Stochastic Search Algorithm Performance using Landscape State Machines

David W. Corne, Joshua D. Knowles, William Rowe, 2006, 2006 IEEE International Conference on Evolutionary Computation.

Learning in Multiobjective Optimization (Dagstuhl Seminar 12041)

Kaisa Miettinen, Eckart Zitzler, Joshua D. Knowles, 2012, Dagstuhl Reports.

Investigations into the Effect of Multiobjectivization in Protein Structure Prediction

Joshua D. Knowles, Julia Handl, Simon C. Lovell, 2008, PPSN.

Experimental optimization by evolutionary algorithms

Ofer M. Shir, Thomas Bäck, Joshua D. Knowles, 2010, GECCO '10.

On the Performance of Ant-based Clustering

Marco Dorigo, Joshua D. Knowles, Julia Handl, 2003, HIS.

A Comparison of the Performance of Different Metaheuristics on the Timetabling Problem

Ben Paechter, Thomas Stützle, Luca Maria Gambardella, 2002, PATAT.

On the Assessment of Multiobjective Approaches to the Adaptive Distributed Database Management Problem

Martin J. Oates, David W. Corne, Joshua D. Knowles, 2000, PPSN.

On the Utility of Redundant Encodings in Mutation-Based Evolutionary Search

Richard A. Watson, Joshua D. Knowles, R. Watson, 2002, PPSN.

Simheuristics for the Multiobjective Nondeterministic Firefighter Problem in a Time-Constrained Setting

Krzysztof Michalak, Joshua D. Knowles, 2016, EvoApplications.

Properties of an adaptive archiving algorithm for storing nondominated vectors

David W. Corne, Joshua D. Knowles, 2003, IEEE Trans. Evol. Comput..

Personalized Multiobjective Optimization: An Analytics Perspective (Dagstuhl Seminar 18031)

Günter Rudolph, Kathrin Klamroth, Joshua D. Knowles, 2018, Dagstuhl Reports.

Global Network Cooperation Catalysed by a Small Prosocial Migrant Clique pdf

Steve Miller, Joshua D. Knowles, 2016, UCNC.

Policy learning in resource-constrained optimization

Joshua D. Knowles, Richard Allmendinger, 2011, GECCO '11.

Multiobjective optimization: When objectives exhibit non-uniform latencies

Joshua D. Knowles, Richard Allmendinger, Julia Handl, 2015, Eur. J. Oper. Res..

The landscape adaptive particle swarm optimizer

Douglas B. Kell, Joshua D. Knowles, Hongmei Lu, 2008, Appl. Soft Comput..

Towards Landscape Analyses to Inform the Design of Hybrid Local Search for the Multiobjective Quadratic Assignment Problem

David W. Corne, Joshua D. Knowles, 2002, HIS.

Closed-loop evolutionary multiobjective optimization

Joshua D. Knowles, 2009, IEEE Computational Intelligence Magazine.

How Much Should You Select for Evolvability?

Andrew M. Webb, Joshua D. Knowles, Julia Handl, 2015, ECAL.

Generating, Maintaining, and Exploiting Diversity in a Memetic Algorithm for Protein Structure Prediction

Joshua D. Knowles, Mario Garza-Fabre, Julia Handl, 2016, Evolutionary Computation.

Selected Aspects of Natural Computing

Xin Yao, Kalyanmoy Deb, David W. Corne, 2012, Handbook of Natural Computing.

Evolutionary Clustering

David W. Corne, Joshua D. Knowles, Julia Handl, 2010, Encyclopedia of Machine Learning.

Evolutionary Multiobjective Clustering

Joshua D. Knowles, Julia Handl, 2004, PPSN.

Quality Assessment of Pareto Set Approximations

Lothar Thiele, Eckart Zitzler, Joshua D. Knowles, 2008, Multiobjective Optimization.

On-Line Purchasing Strategies for an Evolutionary Algorithm Performing Resource-Constrained Optimization

Joshua D. Knowles, Richard Allmendinger, 2010, PPSN.

Using Machine Learning to Explore the Relevance of Local and Global Features During Conformational Search in Rosetta

Joshua D. Knowles, Mario Garza-Fabre, Julia Handl, 2015, GECCO.

Accuracy and tractability of a kriging model of intramolecular polarizable multipolar electrostatics and its application to histidine

Joshua D. Knowles, Yongna Yuan, Paul L. A. Popelier, 2013, J. Comput. Chem..

No Free Lunch and Free Leftovers Theorems for Multiobjective Optimisation Problems

David W. Corne, Joshua D. Knowles, 2003, EMO.

Heuristics for Evolutionary Off-line Routing in Telecommunication Networks

David W. Corne, Joshua D. Knowles, 2000, GECCO.

Enumeration of Pareto optimal multi-criteria spanning trees - a proof of the incorrectness of Zhou and Gen's proposed algorithm

David W. Corne, Joshua D. Knowles, 2002, Eur. J. Oper. Res..

Local search for the probabilistic traveling salesman problem: Correction to the 2-p-opt and 1-shift algorithms

Joshua D. Knowles, Leonora Bianchi, Neill Bowler, 2005, Eur. J. Oper. Res..

Deep Optimisation: Solving Combinatorial Optimisation Problems using Deep Neural Networks pdf

Richard A. Watson, Joshua D. Knowles, J. R. Caldwell, 2018, ArXiv.

Noisy Multiobjective Optimization on a Budget of 250 Evaluations

David W. Corne, Joshua D. Knowles, Alan P. Reynolds, 2009, EMO.

A new evolutionary approach to the degree-constrained minimum spanning tree problem

David W. Corne, Joshua D. Knowles, 2000, IEEE Trans. Evol. Comput..

The Pareto Envelope-Based Selection Algorithm for Multi-objective Optimisation

Martin J. Oates, David W. Corne, Joshua D. Knowles, 2000, PPSN.

Approximating the Nondominated Front Using the Pareto Archived Evolution Strategy

David W. Corne, Joshua D. Knowles, D. Corne, 2000, Evolutionary Computation.

Reducing Local Optima in Single-Objective Problems by Multi-objectivization

Richard A. Watson, David W. Corne, Joshua D. Knowles, 2001, EMO.

09041 Working Group on EMO for Robust Multiobjective Optimization (1st Round)

Nirupam Chakraborti, Nicola Beume, Kalyanmoy Deb, 2009, Hybrid and Robust Approaches to Multiobjective Optimization.

Multiobjective Optimization on a Budget of 250 Evaluations

Joshua D. Knowles, Evan J. Hughes, E. Hughes, 2005, EMO.

Evolutionary Optimization on Problems Subject to Changes of Variables

Joshua D. Knowles, Richard Allmendinger, 2010, PPSN.

Rapid Skill Capture in a First-Person Shooter

Ke Chen, Joshua D. Knowles, David Buckley, 2017, IEEE Transactions on Computational Intelligence and AI in Games.

Editorial

Dimo Brockhoff, Joshua D. Knowles, Boris Naujoks, 2017, Comput. Oper. Res..

Multiobjective Optimization in Bioinformatics and Computational Biology

Douglas B. Kell, Joshua D. Knowles, Julia Handl, 2007, IEEE ACM Trans. Comput. Biol. Bioinform..

Clustering Criteria in Multiobjective Data Clustering

Joshua D. Knowles, Julia Handl, 2012, PPSN.

Multiobjective clustering around medoids

Joshua D. Knowles, Julia Handl, 2005, 2005 IEEE Congress on Evolutionary Computation.

An Evolutionary Approach to Multiobjective Clustering

Joshua D. Knowles, Julia Handl, Julia Handl, 2007, IEEE Transactions on Evolutionary Computation.

A summary-attainment-surface plotting method for visualizing the performance of stochastic multiobjective optimizers

Joshua D. Knowles, 2005, 5th International Conference on Intelligent Systems Design and Applications (ISDA'05).

A metabolome pipeline: from concept to data to knowledge

Douglas B. Kell, Joshua D. Knowles, Irena Spasić, 2005, Metabolomics.

Multi-Objective Clustering and Cluster Validation

Joshua D. Knowles, Julia Handl, J. Handl, 2006, Multi-Objective Machine Learning.

Systematic construction of algorithm portfolios for a Maintenance Scheduling Problem

Joshua D. Knowles, Ahmad Almakhlafi, 2013, 2013 IEEE Congress on Evolutionary Computation.

Quantifying the Effects of Objective Space Dimension in Evolutionary Multiobjective Optimization

David W. Corne, Joshua D. Knowles, 2006, EMO.

Improvements to the scalability of multiobjective clustering

Joshua D. Knowles, Julia Handl, 2005, 2005 IEEE Congress on Evolutionary Computation.

The Emergence of Cooperation in Public Goods Games on Randomly Growing Dynamic Networks

Steve Miller, Joshua D. Knowles, 2016, EvoApplications.

Molecular Structure Elucidation Using Ant Colony Optimization: A Preliminary Study

Douglas B. Kell, Joshua D. Knowles, Caroline Farrelly, 2008, ANTS Conference.

Predicting skill from gameplay input to a first-person shooter

Ke Chen, Joshua D. Knowles, David Buckley, 2013, 2013 IEEE Conference on Computational Inteligence in Games (CIG).

Instance Generators and Test Suites for the Multiobjective Quadratic Assignment Problem

David W. Corne, Joshua D. Knowles, 2003, EMO.

Machine Decision Makers as a Laboratory for Interactive EMO

Manuel López-Ibáñez, Joshua D. Knowles, 2015, EMO.

Semi-supervised feature selection via multiobjective optimization

Joshua D. Knowles, Julia Handl, 2006, The 2006 IEEE International Joint Conference on Neural Network Proceedings.

Multiobjectivization by Decomposition of Scalar Cost Functions

Joshua D. Knowles, Julia Handl, Simon C. Lovell, 2008, PPSN.

Ant-Based Clustering and Topographic Mapping

Marco Dorigo, Joshua D. Knowles, Julia Handl, 2006, Artificial Life.

Comparing multi-objective and threshold-moving ROC curve generation for a prototype-based classifier

Joshua D. Knowles, Ricardo Aler, Julia Handl, 2013, GECCO '13.

Computational cluster validation in post-genomic data analysis

Douglas B. Kell, Joshua D. Knowles, Julia Handl, 2005, Bioinform..

On semi-supervised clustering via multiobjective optimization

Joshua D. Knowles, Julia Handl, 2006, GECCO '06.

Evolutionary Clustering

David W. Corne, Joshua D. Knowles, Julia Handl, 2017, Encyclopedia of Machine Learning and Data Mining.

Swarm intelligence theory: A snapshot of the state of the art

Riccardo Poli, David W. Corne, Joshua D. Knowles, 2010, Theor. Comput. Sci..

Understanding Complexity in Multiobjective Optimization (Dagstuhl Seminar 15031)

Günter Rudolph, Kathrin Klamroth, Joshua D. Knowles, 2015, Dagstuhl Reports.

'Hang On a Minute': Investigations on the Effects of Delayed Objective Functions in Multiobjective Optimization

Joshua D. Knowles, Richard Allmendinger, 2013, EMO.

Evolutionary Search in Lethal Environments

Joshua D. Knowles, Richard Allmendinger, 2011, IJCCI.

An Investigation of Representations and Operators for Evolutionary Data Clustering with a Variable Number of Clusters

Joshua D. Knowles, Julia Handl, 2006, PPSN.

Benchmarks for maintenance scheduling problems in power generation

Joshua D. Knowles, Ahmad Almakhlafi, 2012, 2012 IEEE Congress on Evolutionary Computation.

On Using Decision Maker Preferences with ParEGO

Joshua D. Knowles, Jussi Hakanen, 2017, EMO.

Techniques for highly multiobjective optimisation: some nondominated points are better than others

David W. Corne, Joshua D. Knowles, 2007, GECCO '07.

On Sequential Online Archiving of Objective Vectors

Marco Laumanns, Manuel López-Ibáñez, Joshua D. Knowles, 2011, EMO.

Evidence Accumulation in Multiobjective Data Clustering

Joshua D. Knowles, Julia Handl, 2013, EMO.

A Minimal Model for the Emergence of Cooperation in Randomly Growing Networks

Steve Miller, Joshua D. Knowles, 2015, ECAL.

Artefacts and biases affecting the evaluation of scoring functions on decoy sets for protein structure prediction

Joshua D. Knowles, Julia Handl, Simon C. Lovell, 2009, Bioinform..

Priority Elicitation in the AHP by a Pareto Envelope-Based Selection Algorithm

Joshua D. Knowles, Ludmil Mikhailov, 2008, MCDM.

Local-search and hybrid evolutionary algorithms for Pareto optimization

Joshua D. Knowles, 2002 .

Strategies for the Increased Robustness of Ant-Based Clustering

Marco Dorigo, Joshua D. Knowles, Julia Handl, 2003, Engineering Self-Organising Systems.

Deep Optimisation: Multi-scale Evolution by Inducing and Searching in Deep Representations

Richard A. Watson, Joshua D. Knowles, Christoph Thies, 2021, EvoApplications.

On metrics for comparing nondominated sets

Joshua D. Knowles, D. Corne, 2002, Proceedings of the 2002 Congress on Evolutionary Computation. CEC'02 (Cat. No.02TH8600).

M-PAES: a memetic algorithm for multiobjective optimization

Joshua D. Knowles, D. Corne, 2000, Proceedings of the 2000 Congress on Evolutionary Computation. CEC00 (Cat. No.00TH8512).

Bounded archiving using the lebesgue measure

Joshua D. Knowles, D. Corne, M. Fleischer, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

Efficient discovery of anti-inflammatory small molecule combinations using evolutionary computing

Joshua D. Knowles, D. Kell, P. Mendes, 2011, Nature chemical biology.

A comparison of encodings and algorithms for multiobjective minimum spanning tree problems

Joshua D. Knowles, D. Corne, 2001, Proceedings of the 2001 Congress on Evolutionary Computation (IEEE Cat. No.01TH8546).

The Pareto archived evolution strategy: a new baseline algorithm for Pareto multiobjective optimisation

David Corne, Joshua D. Knowles, Joshua Knowles, 1999, Proceedings of the 1999 Congress on Evolutionary Computation-CEC99 (Cat. No. 99TH8406).

Evolutionary Computing

Subbarao Kambhampati, Krzysztof Krawiec, Moshe Sipper, 1997, Lecture Notes in Computer Science.

Fifty years of pulsar candidate selection: from simple filters to a new principled real-time classification approach

Joshua D. Knowles, J. M. Brooke, B. Stappers, 2016, Monthly Notices of the Royal Astronomical Society.

Memetic Algorithms for Multiobjective Optimization: Issues, Methods and Prospects

Joshua D. Knowles, David Corne, Joshua Knowles, 2004 .

Some multiobjective optimizers are better than others

Joshua D. Knowles, D. Corne, 2003, The 2003 Congress on Evolutionary Computation, 2003. CEC '03..

ParEGO: a hybrid algorithm with on-line landscape approximation for expensive multiobjective optimization problems

Joshua D. Knowles, J. Knowles, 2006, IEEE Transactions on Evolutionary Computation.

Closed-loop, multiobjective optimization of analytical instrumentation: gas chromatography/time-of-flight mass spectrometry of the metabolomes of human serum and of yeast fermentations.

Joshua D. Knowles, D. Kell, W. Dunn, 2005, Analytical chemistry.

Local search for the probabilistic traveling salesman problem: a proof of the incorrectness of Bertsimas' proposed 2-p-opt and 1-shift algorithms.

Joshua D. Knowles, L. Bianchi, 2002 .

Multiobjective evolutionary optimisation for surface-enhanced Raman scattering

Joshua D. Knowles, R. Goodacre, W. Rowe, 2010, Analytical and bioanalytical chemistry.

Development of a robust and repeatable UPLC-MS method for the long-term metabolomic study of human serum.

Joshua D. Knowles, D. Kell, W. Dunn, 2009, Analytical chemistry.

Exploiting Genomic Knowledge in Optimising Molecular Breeding Programmes: Algorithms from Evolutionary Computing

Joshua D. Knowles, D. Kell, S. O’Hagan, 2012, PloS one.

In silico modelling of directed evolution: Implications for experimental design and stepwise evolution.

Douglas B. Kell, Joshua D. Knowles, Joshua Knowles, 2009, Journal of theoretical biology.

The role of modeling in systems biology

Douglas B. Kell, Joshua D. Knowles, Joshua Knowles, 2005 .

Personalized Multiobjective Optimization: An Analytics Perspective

Joshua D. Knowles, G. Rudolph, M. Wiecek, 2018 .

Molecular phenotyping of a UK population: defining the human serum metabolome

Douglas B. Kell, Joshua D. Knowles, Ian D. Wilson, 2014, Metabolomics.

THE ROLE OF MODELING IN SYSTEMS BIOLOGY 3 1 . 1 Philosophical overview

Joshua D. Knowles, D. Kell, 2005 .

University of Birmingham Understanding Complexity in Multiobjective Optimization

Joshua D. Knowles, G. Rudolph, S. Greco, 2015 .

University of Birmingham Population fluctuation promotes cooperation in networks

Joshua D. Knowles, Steve Miller, 2015 .

Cooperative Multi-Agent Search on Endogenously-Changing Fitness Landscapes

Joshua D. Knowles, R. Allmendinger, M. Bleda, 2022, PPSN.

Multiobjective Problem Solving from Nature: From Concepts to Applications

Kalyanmoy Deb, David Corne, Joshua D. Knowles, 2008, Natural Computing Series.

Expensive optimization with production-graph resource constraints: a first look at a new problem class

Joshua D. Knowles, M. López-Ibáñez, R. Allmendinger, 2022, GECCO.

The good of the many outweighs the good of the one: evolutionary multi-objective optimization

P. J. Fleming, David Corne, Joshua D. Knowles, 2003 .

A Study on Classification in Imbalanced and Partially-Labelled Data Streams

Joshua D. Knowles, J. M. Brooke, B. W. Stappers, 2013, 2013 IEEE International Conference on Systems, Man, and Cybernetics.

Procedures for large-scale metabolic profiling of serum and plasma using gas chromatography and liquid chromatography coupled to mass spectrometry

Joshua D. Knowles, D. Kell, R. Goodacre, 2011, Nature Protocols.

Insights into the behaviour of systems biology models from dynamic sensitivity and identifiability analysis: a case study of an NF-kappaB signalling pathway.

Hong Wang, Martin Brown, Joshua D. Knowles, 2006, Molecular bioSystems.

Analysis of a complete DNA–protein affinity landscape

Joshua D. Knowles, D. Kell, J. Knowles, 2010, Journal of The Royal Society Interface.

Evaluation Data

Joshua D. Knowles, S. Kambhampati, T. Heskes, 2010, Encyclopedia of Machine Learning.

52 Selected Aspects of Natural

Joshua D. Knowles, Kalyanmoy Deb, Joshua Knowles, 2012 .

Predictive models for population performance on real biological fitness landscapes

Douglas B. Kell, Joshua D. Knowles, William Rowe, 2010, Bioinform..

Development and performance of a gas chromatography-time-of-flight mass spectrometry analysis for large-scale nontargeted metabolomic studies of human serum.

Joshua D. Knowles, Royston Goodacre, Douglas B Kell, 2009, Analytical chemistry.