Tim Hendtlass - researchr alias

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Viewing Publication 1 - 71 from 71

2022

Measuring the Effects of Increasing Dimensionality on Fitness-Based Selection and Failed ExplorationStephen Chen 0001, Antonio Bolufé Röhler, James Montgomery, Dania Tamayo-Vera, Tim Hendtlass. cec 2022: 1-8 [doi]

Using Average-Fitness Based Selection to Combat the Curse of DimensionalityStephen Chen 0001, Antonio Bolufé Röhler, James Montgomery, Wenxuan Zhang, Tim Hendtlass. cec 2022: 1-8 [doi]

2021

A Random Walk Analysis of Search in MetaheuristicsStephen Chen 0001, Shehnaz Islam, Antonio Bolufé Röhler, James Montgomery, Tim Hendtlass. cec 2021: 2323-2330 [doi]

2020

Evolving Musical Sight Reading Exercises Using Expert ModelsCharlotte Pierce, Tim Hendtlass, Anthony Bartel, Clinton J. Woodward. frai, 3:497530, 2020. [doi]

2019

An Analysis on the Effect of Selection on Exploration in Particle Swarm Optimization and Differential EvolutionStephen Chen 0001, Antonio Bolufé Röhler, James Montgomery, Tim Hendtlass. cec 2019: 3037-3044 [doi]

The EZopt Optimisation FrameworkTim Hendtlass. cec 2019: 3110-3117 [doi]

2018

Improved Exploration and Exploitation in Particle Swarm OptimizationDania Tamayo-Vera, Stephen Chen, Antonio Bolufé Röhler, James Montgomery, Tim Hendtlass. ieaaie 2018: 421-433 [doi]

2016

A network that uses parametric weightsTim Hendtlass, Hans Pierrot. ijcnn 2016: 60-67 [doi]

2012

Improving exploration in Ant Colony Optimisation with antennationChristopher Beer, Tim Hendtlass, James Montgomery. cec 2012: 1-8 [doi]

Restarting Particle Swarm Optimisation for deceptive problemsTim Hendtlass. cec 2012: 1-9 [doi]

2009

A Heterogeneous Particle SwarmLuke Cartwright, Tim Hendtlass. ACAL 2009: 201-210 [doi]

Quantised Problem Spaces and the Particle Swarm AlgorithmTim Hendtlass. In Raymond Chiong, Sandeep Dhakal, editors, Natural Intelligence for Scheduling, Planning and Packing Problems. Volume 250 of Studies in Computational Intelligence, pages 175-193, Springer, 2009. [doi]

Particle Swarm Optimisation and high dimensional problem spacesTim Hendtlass. cec 2009: 1988-1994 [doi]

2008

The Particle Swarm AlgorithmTim Hendtlass. In John Fulcher, Lakhmi C. Jain, editors, Computational Intelligence: A Compendium. Volume 115 of Studies in Computational Intelligence, pages 1029-1062, Springer, 2008. [doi]

Extremal Optimisation and Bin PackingTim Hendtlass, Marcus Randall. seal 2008: 220-228 [doi]

Collective intelligence and bush fire spottingDavid Howden, Tim Hendtlass. gecco 2008: 41-48 [doi]

Solution bias in ant colony optimisation: Lessons for selecting pheromone modelsJames Montgomery, Marcus Randall, Tim Hendtlass. cor, 35(9):2728-2749, 2008. [doi]

An evolutionary reincarnation algorithmBen Prime, Tim Hendtlass. cec 2008: 737-743 [doi]

2007

Fitness estimation and the particle swarm optimisation algorithmTim Hendtlass. cec 2007: 4266-4272 [doi]

A simple and efficient multi-component algorithm for solving dynamic function optimisation problemsIrene Moser, Tim Hendtlass. cec 2007: 252-259 [doi]

Solving Dynamic Single-Runway Aircraft Landing Problems With Extremal OptimisationIrene Moser, Tim Hendtlass. cisched 2007: 206-211 [doi]

Mechanisms for Evolutionary ReincarnationBen Prime, Tim Hendtlass. ACAL 2007: 245-256 [doi]

2006

Waves of Swarm Particles (WoSP)Tim Hendtlass. In Nadia Nedjah, Luiza de Macedo Mourelle, editors, Swarm Intelligent Systems. Volume 26 of Studies in Computational Intelligence, pages 27-58, Springer, 2006. [doi]

A Particle Swarm Algorithm for Complex Quantised Problem SpacesTim Hendtlass. cec 2006: 1015-1019 [doi]

Dynamic Problems and Nature Inspired Meta-HeuristicsTim Hendtlass, Irene Moser, Marcus Randall. eScience 2006: 111 [doi]

Solving Problems with Hidden Dynamics - Comparison of Extremal Optimisation and Ant Colony SystemIrene Moser, Tim Hendtlass. cec 2006: 1248-1255 [doi]

On the Behaviour of Extremal Optimisation When Solving Problems with Hidden DynamicsIrene Moser, Tim Hendtlass. ieaaie 2006: 292-301 [doi]

Using a modified counter-propagation algorithm to classify conjoined dataHans Pierrot, Tim Hendtlass. apin, 24(3):241-251, 2006. [doi]

2005

Dynamic Ant Colony OptimisationDaniel Angus, Tim Hendtlass. apin, 23(1):33-38, 2005. [doi]

Developments in Applied Artificial Intelligence: Guest Editor s IntroductionTim Hendtlass. apin, 23(1):7-8, 2005. [doi]

WoSP: a multi-optima particle swarm algorithmTim Hendtlass. cec 2005: 727-734 [doi]

A particle swarm algorithm for high dimensional, multi-optima problem spacesTim Hendtlass. kit 2005: 149-154 [doi]

Structural Advantages for Ant Colony Optimisation Inherent in Permutation Scheduling ProblemsJames Montgomery, Marcus Randall, Tim Hendtlass. ieaaie 2005: 218-228 [doi]

Automated Selection of Appropriate Pheromone Representations in Ant Colony OptimizationJames Montgomery, Marcus Randall, Tim Hendtlass. alife, 11(3):269-291, 2005. [doi]

The Fast Evaluation Strategy for Evolvable HardwareMehrdad Salami, Tim Hendtlass. gpem, 6(2):139-162, 2005. [doi]

2004

2003

Combining a Rule-Based Expert System and Machine Learning in a Simulated Mobile Robot Control SystemK. Foster, Tim Hendtlass. his 2003: 361-370

Preserving Diversity in Particle Swarm OptimisationTim Hendtlass. ieaaie 2003: 31-40 [doi]

Using a Modified Counter-Propagation Algorithm to Classify Conjoint DataHans Pierrot, Tim Hendtlass. ieaaie 2003: 337-347 [doi]

A fast evaluation strategy for evolutionary algorithmsMehrdad Salami, Tim Hendtlass. asc, 2(3):156-173, 2003. [doi]

2002

2001

A Combined Swarm Differential Evolution Algorithm for Optimization ProblemsTim Hendtlass. ieaaie 2001: 11-18 [doi]

Enhanced Artificial Neurons for Network ApplicationsGerard Murray, Tim Hendtlass. ieaaie 2001: 281-289 [doi]

Dynamic Trait Expression for Multiploid Individuals of Evolutionary AlgorithmsClinton Woodward, Tim Hendtlass. ieaaie 2001: 374-382 [doi]

2000

SOMulANT: Organizing Information Using Multiple AgentsTim Hendtlass. ieaaie 2000: 322-327 [doi]

1999

The Parallel Path Artificial MicronetGerard Murray, Tim Hendtlass, John R. Podlena. ieaaie 1999: 111-117

1998

An Evolutionary Algorithm with a Genetic Encoding SchemeHoward Copeland, Tim Hendtlass. ieaaie 1998: 632-639

Generating Lookup Tables Using Evolutionary AlgorithmsTim Hendtlass. ieaaie 1998: 640-646

Ensembles of Neural Networks for Analogue ProblemsDavid Philpot, Tim Hendtlass. ieaaie 1998: 625-631

An Accelerated Genetic AlgorithmJohn R. Podlena, Tim Hendtlass. apin, 8(2):103-111, 1998.

1997

Migration through Mutation Space: A Means of Accelerating Convergence in Evolutionary AlgorithmsHoward Copland, Tim Hendtlass. icannga 1998: 183-187 [doi]

Using Evolution to Develop Look Up Tables for Congruent Data SetsTim Hendtlass. iconip 1998: 397-400

Ensembles of Neural Networks for Digital ProblemsDavid Philpot, Tim Hendtlass. icannga 1998: 31-34 [doi]

Using Hierarchical Genetic Populations to Improve Solution QualityJohn R. Podlena, Tim Hendtlass. icannga 1998: 198-201 [doi]

1996

Better Neurons for Biological SimulationsHoward Copeland, Tim Hendtlass. ieaaie 1996: 795

An Evolutionary Algorithm for The Generation of Unsupervised Self Organizing Neural NetsTim Hendtlass. ieaaie 1996: 537-542

A Cascade of Neural Networks for Complex ClassificationDavid Philpot, Tim Hendtlass. ieaaie 1996: 791

Using The Baldwin Effect to Accelerate A Genetic AlgorithmJohn R. Podlena, Tim Hendtlass. ieaaie 1996: 253-260

1995

Engram decay in artificial neural networksHoward Copland, Tim Hendtlass. icnn 1995: 669-673 [doi]

A self organizing artificial neural network with problem dependent structureTim Hendtlass. icnn 1995: 1111-1115 [doi]

Using a Combination of Genetic Algorithm and Hill Climbing Techniques for the Solution of a Difficult Letter Recognition ProblemJohn R. Podlena, Tim Hendtlass. ieaaie 1995: 55-60 [doi]

1993

A low cost distributed expert system delivery environment for monitoring and control applicationsTim Hendtlass, Simon Goss. annes 1993: 312-313 [doi]

The discrimination of short acoustic events by artificial neural networksTim Hendtlass, Janice Wells. annes 1993: 109-112 [doi]

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