default search action
Michael Kirley
Person information
- affiliation: University of Melbourne, School of Computing and Information Systems, Australia
- affiliation (former): Charles Sturt University, School of Environmental and Information Sciences, Albury, NSW, Australia
Refine list
refinements active!
zoomed in on ?? of ?? records
view refined list in
export refined list as
showing all ?? records
2020 – today
- 2024
- [j27]Daniel Herring
, Michael Kirley
A comparative study of evolutionary approaches to the bi-objective dynamic Travelling Thief Problem. Swarm Evol. Comput. 84: 101433 (2024) - [c79]Behzad Moradi
Sensitivity Analysis of Surrogate-assisted Bilevel Optimisation. GECCO Companion 2024: 411-414 - [c78]Hanan Alsouly
Online Per-Instance Algorithm Selection for Constrained Multi-Objective Optimization Problems. GECCO Companion 2024: 559-562 - [c77]Yige Song
A Case Study on University Student Online Learning Patterns Across Multidisciplinary Subjects. LAK 2024: 936-942 - 2023
- [j26]Hanan Alsouly
An Instance Space Analysis of Constrained Multiobjective Optimization Problems. IEEE Trans. Evol. Comput. 27(5): 1427-1439 (2023) - [c76]Helani Wickramaarachchi
Cooperative Multi-Agent Reinforcement Learning with Dynamic Target Localization: A Reward Sharing Approach. AI (2) 2023: 310-324 - [c75]Hanan Alsouly, Michael Kirley, Mario Andrés Muñoz:
Dynamic Landscape Analysis for Constrained Multiobjective Optimization Problems. AI (1) 2023: 429-441 - [c74]Shuchang Shen, Sachith Seneviratne, Xinye Wanyan, Michael Kirley:
FireRisk: A Remote Sensing Dataset for Fire Risk Assessment with Benchmarks Using Supervised and Self-supervised Learning. DICTA 2023: 189-196 - [c73]Daniel Herring
An Iterative Machine Learning Approach to Informative Performance Reporting in Dynamic Multi-Objective Optimization. GECCO Companion 2023: 367-370 - [i8]Xinye Wanyan, Sachith Seneviratne, Shuchang Shen, Michael Kirley:
DINO-MC: Self-supervised Contrastive Learning for Remote Sensing Imagery with Multi-sized Local Crops. CoRR abs/2303.06670 (2023) - [i7]Shuchang Shen, Sachith Seneviratne, Xinye Wanyan, Michael Kirley:
FireRisk: A Remote Sensing Dataset for Fire Risk Assessment with Benchmarks Using Supervised and Self-supervised Learning. CoRR abs/2303.07035 (2023) - 2022
- [j25]Yuan Sun
Boosting ant colony optimization via solution prediction and machine learning. Comput. Oper. Res. 143: 105769 (2022) - [j24]Mario Andrés Muñoz
Analyzing randomness effects on the reliability of exploratory landscape analysis. Nat. Comput. 21(2): 131-154 (2022) - [j23]Irina Grossman, Kasun Bandara
Can machine learning improve small area population forecasts? A forecast combination approach. Comput. Environ. Urban Syst. 95: 101806 (2022) - [c72]Lige Tan, Ben Ko, Guilherme Luz Tortorella, Abel Cervantes, Martin Palmer, Michael Kirley:
Statistical Modelling for Simulating and Interpreting an Egg Packaging Process for Giveaway Mitigation. ACIS 2022: 70 - [c71]Daniel Herring
Analysing Multiobjective Optimization Using Evolutionary Path Length Correlation. AI 2022: 467-479 - [c70]Daniel Herring
Reproducibility and baseline reporting for dynamic multi-objective benchmark problems. GECCO 2022: 529-537 - [i6]Hanan Alsouly, Michael Kirley, Mario Andrés Muñoz:
An Instance Space Analysis of Constrained Multi-Objective Optimization Problems. CoRR abs/2203.00868 (2022) - [i5]Daniel Herring, Michael Kirley, Xin Yao:
Reproducibility and Baseline Reporting for Dynamic Multi-objective Benchmark Problems. CoRR abs/2204.04140 (2022) - 2021
- [j22]Mario Andrés Muñoz
Sampling Effects on Algorithm Selection for Continuous Black-Box Optimization. Algorithms 14(1): 19 (2021) - [j21]Peta Masters
Extended Goal Recognition: Lessons from Magic. Frontiers Artif. Intell. 4: 730990 (2021) - [c69]Peta Masters, Michael Kirley, Wally Smith:
Extended Goal Recognition: A Planning-Based Model for Strategic Deception. AAMAS 2021: 871-879 - 2020
- [c68]Yuan Sun, Wei Wang, Michael Kirley, Xiaodong Li, Jeffrey Chan:
Revisiting Probability Distribution Assumptions for Information Theoretic Feature Selection. AAAI 2020: 5908-5915 - [c67]Hadi Akbarzadeh Khorshidi
Machine learning with incomplete datasets using multi-objective optimization models. IJCNN 2020: 1-8 - [c66]Daniel Herring
Responsive Multi-population Models for the Dynamic Travelling Thief Problem. SSCI 2020: 297-304 - [i4]Daniel Herring, Michael Kirley, Xin Yao:
Dynamic Multi-objective Optimization of the Travelling Thief Problem. CoRR abs/2002.02636 (2020) - [i3]Yuan Sun, Sheng Wang, Yunzhuang Shen, Xiaodong Li, Andreas T. Ernst, Michael Kirley:
Boosting Ant Colony Optimization via Solution Prediction and Machine Learning. CoRR abs/2008.04213 (2020) - [i2]Hadi Akbarzadeh Khorshidi, Michael Kirley, Uwe Aickelin:
Machine learning with incomplete datasets using multi-objective optimization models. CoRR abs/2012.13352 (2020)
2010 – 2019
- 2019
- [c65]Hanwei Zhu, Michael Kirley:
Deep Multi-agent Reinforcement Learning in a Common-Pool Resource System. CEC 2019: 142-149 - [c64]Daniel Herring
Investigation of Asynchrony in Dynamic Multi-Objective Optimization. CEC 2019: 3165-3172 - 2018
- [j20]Yuan Sun
A Recursive Decomposition Method for Large Scale Continuous Optimization. IEEE Trans. Evol. Comput. 22(5): 647-661 (2018) - [j19]Manuel Chica
A Networked N-Player Trust Game and Its Evolutionary Dynamics. IEEE Trans. Evol. Comput. 22(6): 866-878 (2018) - [c63]Yuan Sun, Mohammad Nabi Omidvar
Adaptive threshold parameter estimation with recursive differential grouping for problem decomposition. GECCO 2018: 889-896 - [c62]Yuan Sun, Michael Kirley, Xiaodong Li
Cooperative co-evolution with online optimizer selection for large-scale optimization. GECCO 2018: 1079-1086 - 2017
- [j18]Yuan Sun
Quantifying Variable Interactions in Continuous Optimization Problems. IEEE Trans. Evol. Comput. 21(2): 249-264 (2017) - [c61]Camilo Cruz
Generation and Exploration of Architectural Form Using a Composite Cellular Automata. ACALCI 2017: 99-110 - [c60]Yuan Sun, Michael Kirley, Saman K. Halgamuge:
A Memetic Cooperative Co-evolution Model for Large Scale Continuous Optimization. ACALCI 2017: 291-300 - [c59]Friedrich Burkhard von der Osten, Michael Kirley, Tim Miller:
The Minds of Many: Opponent Modeling in a Stochastic Game. IJCAI 2017: 3845-3851 - 2016
- [j17]Michael Kirley, Friedrich Burkhard von der Osten:
Risk sensitivity and assortment in social dilemmas. Soft Comput. 20(10): 3775-3786 (2016) - [c58]Mario A. Muñoz
ICARUS: Identification of complementary algorithms by uncovered sets. CEC 2016: 2427-2432 - [c57]Camilo Cruz
A Morphogenetic Design Strategy Using a Composite CA Model. GECCO (Companion) 2016: 17-18 - 2015
- [j16]Raymond Chiong
Promotion of cooperation in social dilemma games via generalised indirect reciprocity. Connect. Sci. 27(4): 417-433 (2015) - [j15]Eduardo Araujo Oliveira
Device Nimbus: An Intelligent Middleware for Smarter Services for Health and Fitness. Int. J. Distributed Sens. Networks 11: 454626:1-454626:16 (2015) - [j14]Mario A. Muñoz
Algorithm selection for black-box continuous optimization problems: A survey on methods and challenges. Inf. Sci. 317: 224-245 (2015) - [j13]Mario A. Muñoz
Exploratory Landscape Analysis of Continuous Space Optimization Problems Using Information Content. IEEE Trans. Evol. Comput. 19(1): 74-87 (2015) - [c56]Eduardo Araujo Oliveira, Fernando Koch, Michael Kirley, Carlos Victor G. dos Passos Barros:
Towards a Middleware for Context-Aware Health Monitoring. CARE/MFSC@AAMAS 2015: 19-30 - [c55]Eduardo Araujo Oliveira, Michael Kirley, Tom Kvan, Justyna Karakiewicz, Carlos Vaz
Distributed and Heterogeneous Data Analysis for Smart Urban Planning. CAAD Futures 2015: 37-54 - [c54]Yuan Sun, Michael Kirley, Saman Kumara Halgamuge:
Extended Differential Grouping for Large Scale Global Optimization with Direct and Indirect Variable Interactions. GECCO 2015: 313-320 - [c53]Yuan Sun, Michael Kirley, Saman Kumara Halgamuge
On the Selection of Decomposition Methods for Large Scale Fully Non-separable Problems. GECCO (Companion) 2015: 1213-1216 - 2014
- [j12]Jens Pfau, Samin Karim, Michael Kirley, Liz Sonenberg:
Improving cognitive agent decision making: Experience trajectories as plans. Web Intell. Agent Syst. 12(3): 267-287 (2014) - [c52]Friedrich Burkhard von der Osten, Michael Kirley, Tim Miller:
Robust anticipatory stigmergic collision avoidance in multi-agent systems. AAMAS 2014: 1403-1404 - [c51]Friedrich Burkhard von der Osten, Michael Kirley, Tim Miller:
Anticipatory stigmergic collision avoidance under noise. GECCO 2014: 65-72 - [c50]Michael Kirley, Friedrich Burkhard von der Osten:
Risk aversion and mobility in the public goods game. GECCO (Companion) 2014: 157-158 - [c49]Eduardo Araujo Oliveira, Michael Kirley, Elena Vanz, Kiev Gama
hSpy: An intelligent framework for context and predictive analysis for smarter health devices. ICTC 2014: 53-58 - [c48]Michael Kirley, Friedrich Burkhard von der Osten:
Adaptive Risk Aversion in Social Dilemmas. SEAL 2014: 443-454 - 2013
- [j11]Md. Rafiul Hassan, Baikunth Nath, Michael Kirley, Joarder Kamruzzaman
Erratum to "A hybrid of multiobjective Evolutionary Algorithm and HMM-Fuzzy model for time series prediction" [Neurocomputing, 81 (2012) (1-11)]. Neurocomputing 122: 545 (2013) - [j10]Mani Abedini, Michael Kirley:
An enhanced XCS rule discovery module using feature ranking. Int. J. Mach. Learn. Cybern. 4(3): 173-187 (2013) - [c47]Mani Abedini, Michael Kirley, Raymond Chiong
GPU-accelerated eXtended Classifier System. CIDM 2013: 293-300 - [c46]Raymond Chiong
A Multi-agent Based Migration Model for Evolving Cooperation in the Spatial N-Player Snowdrift Game. PRIMA 2013: 70-84 - 2012
- [j9]Md. Rafiul Hassan, Baikunth Nath, Michael Kirley, Joarder Kamruzzaman
A hybrid of multiobjective Evolutionary Algorithm and HMM-Fuzzy model for time series prediction. Neurocomputing 81: 1-11 (2012) - [j8]Raymond Chiong
Effects of Iterated Interactions in Multiplayer Spatial Evolutionary Games. IEEE Trans. Evol. Comput. 16(4): 537-555 (2012) - [c45]Raymond Chiong
The evolution of cooperation via stigmergic interactions. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c44]Mario A. Muñoz
Landscape characterization of numerical optimization problems using biased scattered data. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c43]Minh Van Nguyen, Michael Kirley, Rodolfo García-Flores:
Community evolution in a scientific collaboration network. IEEE Congress on Evolutionary Computation 2012: 1-8 - [c42]Mario A. Muñoz
A Meta-learning Prediction Model of Algorithm Performance for Continuous Optimization Problems. PPSN (1) 2012: 226-235 - 2011
- [j7]Marco Aurélio Stelmar Netto, Christian Vecchiola, Michael Kirley, Carlos A. Varela, Rajkumar Buyya:
Use of run time predictions for automatic co-allocation of multi-cluster resources for iterative parallel applications. J. Parallel Distributed Comput. 71(10): 1388-1399 (2011) - [j6]Mengjie Zhang, Michael Kirley, Xiaodong Li
Guest Editorial: special issue on evolutionary optimisation and learning. Soft Comput. 15(9): 1671-1673 (2011) - [c41]Mani Abedini, Michael Kirley:
Guided Rule Discovery in XCS for High-Dimensional Classification Problems. Australasian Conference on Artificial Intelligence 2011: 1-10 - [c40]Jacob Dumesny, Tim Miller, Michael Kirley, Liz Sonenberg:
TATM: A Trust Mechanism for Social Traders in Double Auctions. Australasian Conference on Artificial Intelligence 2011: 402-411 - [c39]Raymond Chiong
Iterated n-player games on small-world networks. GECCO 2011: 1123-1130 - [c38]Jens Pfau, Michael Kirley, Yoshihisa Kashima:
An Agent-Based Model of Stereotype Communication. PRIMA Workshops 2011: 32-47 - 2010
- [c37]Raymond Chiong, Michael Kirley:
Co-evolution of agent strategies in N-player dilemmas. AAMAS 2010: 1591-1592 - [c36]Raymond Chiong
Evolving Cooperation in the Spatial N-player Snowdrift Game. Australasian Conference on Artificial Intelligence 2010: 263-272 - [c35]Mani Abedini, Michael Kirley:
A multiple population XCS: Evolving condition-action rules based on feature space partitions. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c34]Raymond Chiong
Imitation vs evolution: Analysing the effects of strategy update mechanisms in N-player social dilemmas. IEEE Congress on Evolutionary Computation 2010: 1-8 - [c33]Golriz Rezaei, Jens Pfau, Michael Kirley:
Distributed Advice-Seeking on an Evolving Social Network. IAT 2010: 24-31
2000 – 2009
- 2009
- [j5]A. K. M. Khaled Ahsan Talukder, Michael Kirley, Rajkumar Buyya:
Multiobjective differential evolution for scheduling workflow applications on global Grids. Concurr. Comput. Pract. Exp. 21(13): 1742-1756 (2009) - [j4]Michael Kirley, Mengjie Zhang, Xiaodong Li
Special issue on simulated evolution and learning. Evol. Intell. 2(4): 149-150 (2009) - [j3]Golriz Rezaei, Michael Kirley:
The effects of time-varying rewards on the evolution of cooperation. Evol. Intell. 2(4): 207-218 (2009) - [c32]Raymond Chiong
Co-evolutionary Learning in the N-player Iterated Prisoner's Dilemma with a Structured Environment. ACAL 2009: 32-42 - [c31]Golriz Rezaei, Michael Kirley, Jens Pfau:
Evolving Cooperation in the N-player Prisoner's Dilemma: A Social Network Model. ACAL 2009: 43-52 - [c30]Mani Abedini, Michael Kirley:
CoXCS: A Coevolutionary Learning Classifier Based on Feature Space Partitioning. Australasian Conference on Artificial Intelligence 2009: 360-369 - [c29]A. K. M. Khaled Ahsan Talukder, Michael Kirley, Rajkumar Buyya:
The Pareto-Following Variation Operator as an alternative approximation model. IEEE Congress on Evolutionary Computation 2009: 8-15 - [i1]Christian Vecchiola, Michael Kirley, Rajkumar Buyya:
Multi-Objective Problem Solving With Offspring on Enterprise Clouds. CoRR abs/0903.1386 (2009) - 2008
- [c28]Cherhan Foo, Michael Kirley:
An analysis of the effects of clustering in graph-based evolutionary algorithms. IEEE Congress on Evolutionary Computation 2008: 2246-2253 - [c27]A. K. M. Khaled Ahsan Talukder, Michael Kirley:
A Pareto following variation operator for evolutionary dynamic multi-objective optimization. IEEE Congress on Evolutionary Computation 2008: 2270-2277 - [c26]A. K. M. Khaled Ahsan Talukder, Michael Kirley, Rajkumar Buyya:
A pareto following variation operator for fast-converging multiobjective evolutionary algorithms. GECCO 2008: 721-728 - [c25]M. Maruf Hossain, Md. Rafiul Hassan, Michael Kirley:
Forecasting Urban Air Pollution Using HMM-Fuzzy Model. PAKDD 2008: 572-581 - [c24]Md. Rafiul Hassan, M. Maruf Hossain, Chandan K. Karmakar
Phylogeny Inference Using a Multi-objective Evolutionary Algorithm with Indirect Representation. SEAL 2008: 41-50 - [c23]Golriz Rezaei, Michael Kirley:
Heterogeneous Payoffs and Social Diversity in the Spatial Prisoner's Dilemma game. SEAL 2008: 585-594 - [e1]Xiaodong Li, Michael Kirley, Mengjie Zhang, David G. Green, Victor Ciesielski, Hussein A. Abbass, Zbigniew Michalewicz, Tim Hendtlass, Kalyanmoy Deb, Kay Chen Tan, Jürgen Branke, Yuhui Shi:
Simulated Evolution and Learning, 7th International Conference, SEAL 2008, Melbourne, Australia, December 7-10, 2008. Proceedings. Lecture Notes in Computer Science 5361, Springer 2008, ISBN 978-3-540-89693-7 [contents] - 2007
- [j2]Md. Rafiul Hassan, Baikunth Nath, Michael Kirley:
A fusion model of HMM, ANN and GA for stock market forecasting. Expert Syst. Appl. 33(1): 171-180 (2007) - [c22]Xiaodong Li
On performance metrics and particle swarm methods for dynamic multiobjective optimization problems. IEEE Congress on Evolutionary Computation 2007: 576-583 - [c21]Michael Kirley, Robert L. Stewart:
Multiobjective Evolutionary Algorithms on Complex Networks. EMO 2007: 81-95 - [c20]Robert L. Stewart, Michael Kirley:
Swarming with logic. GECCO 2007: 184 - [c19]Michael Kirley, Robert L. Stewart:
An analysis of the effects of population structure on scalable multiobjective optimization problems. GECCO 2007: 845-852 - [c18]Xiaodong Li
Performance measures and particle swarm methods for dynamic multi-objective optimization problems. GECCO 2007: 907 - [c17]Jia Yu, Michael Kirley, Rajkumar Buyya:
Multi-objective planning for workflow execution on Grids. GRID 2007: 10-17 - [c16]A. K. M. Khaled Ahsan Talukder, Michael Kirley, Rajkumar Buyya:
Multiobjective differential evolution for workflow execution on grids. MGC 2007: 3 - 2006
- [c15]Somesh Selvaratnam, Michael Kirley:
Predicting Stock Market Time Series Using Evolutionary Artificial Neural Networks with Hurst Exponent Input Windows. Australian Conference on Artificial Intelligence 2006: 617-626 - [c14]Harold Soh, Michael Kirley:
moPGA: Towards a New Generation of Multi-objective Genetic Algorithms. IEEE Congress on Evolutionary Computation 2006: 1702-1709 - [c13]Md. Rafiul Hassan, Baikunth Nath, Michael Kirley:
HMM based Fuzzy Model for Time Series Prediction. FUZZ-IEEE 2006: 2120-2126 - [c12]Michael Kirley:
Dominance hierarchies and social diversity in multi-agent systems. GECCO 2006: 159-166 - [c11]Nicole Ronald, Leon Sterling, Michael Kirley:
Evaluating JACK Sim for Agent-Based Modelling of Pedestrians. IAT 2006: 81-87 - [c10]Nicole Ronald, Michael Kirley:
Pedestrian Modelling: A Comparative Study Using Agent-Based Cellular Automata. International Conference on Computational Science (3) 2006: 248-255 - 2005
- [c9]Michael Kirley:
Competition, cooperation and collective behaviour: resource utilization in non-stationary environments. IAT 2005: 572-578 - [c8]Kalyanaraman Kaesava Kshetrapalapuram, Michael Kirley:
Mining Classification Rules Using Evolutionary Multi-objective Algorithms. KES (3) 2005: 959-965 - 2004
- [c7]David Cornforth, Michael Kirley, Terry Bossomaier:
Agent Heterogeneity and Coalition Formation: Investigating Market-Based Cooperative Problem Solving. AAMAS 2004: 556-563 - [c6]David Cornforth, Michael Kirley:
Cooperative Problem Solving Using an Agent-Based Market. GECCO (1) 2004: 60-71 - 2002
- [j1]Michael Kirley:
A Cellular Genetic Algorithm with Disturbances: Optimisation Using Dynamic Spatial Interactions. J. Heuristics 8(3): 321-342 (2002) - [c5]Xiaodong Li
The effects of varying population density in a fine-grained parallel genetic algorithm. IEEE Congress on Evolutionary Computation 2002: 1709-1714 - 2001
- [c4]Michael Kirley:
MEA: a metapopulation evolutionary algorithm for multi-objective optimisation problems. CEC 2001: 949-956 - 2000
- [c3]Michael Kirley, David G. Green:
An Empirical Investigation of Optimization in Dynamic Environments Using the Cellular Genetic Algorithm. GECCO 2000: 11-18
1990 – 1999
- 1999
- [c2]Michael Kirley:
A coevolutiouary genetic algorithm for job shop scheduling problems. KES 1999: 84-87 - 1998
- [c1]Michael Kirley, Xiaodong Li, David G. Green:
Investigation of a Cellular Genetic Algorithm that Mimics Landscape Ecology. SEAL 1998: 90-97
Coauthor Index
Saman K. Halgamuge
aka: Saman Kumara Halgamuge
aka: Saman Kumara Halgamuge
manage site settings
To protect your privacy, all features that rely on external API calls from your browser are turned off by default. You need to opt-in for them to become active. All settings here will be stored as cookies with your web browser. For more information see our F.A.Q.
Unpaywalled article links
Add open access links from to the list of external document links (if available).
Privacy notice: By enabling the option above, your browser will contact the API of unpaywall.org to load hyperlinks to open access articles. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Unpaywall privacy policy.
Archived links via Wayback Machine
For web page which are no longer available, try to retrieve content from the of the Internet Archive (if available).
Privacy notice: By enabling the option above, your browser will contact the API of archive.org to check for archived content of web pages that are no longer available. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Internet Archive privacy policy.
Reference lists
Add a list of references from ,
, and
to record detail pages.
load references from crossref.org and opencitations.net
Privacy notice: By enabling the option above, your browser will contact the APIs of crossref.org, opencitations.net, and semanticscholar.org to load article reference information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the Crossref privacy policy and the OpenCitations privacy policy, as well as the AI2 Privacy Policy covering Semantic Scholar.
Citation data
Add a list of citing articles from and
to record detail pages.
load citations from opencitations.net
Privacy notice: By enabling the option above, your browser will contact the API of opencitations.net and semanticscholar.org to load citation information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the OpenCitations privacy policy as well as the AI2 Privacy Policy covering Semantic Scholar.
OpenAlex data
Load additional information about publications from .
Privacy notice: By enabling the option above, your browser will contact the API of openalex.org to load additional information. Although we do not have any reason to believe that your call will be tracked, we do not have any control over how the remote server uses your data. So please proceed with care and consider checking the information given by OpenAlex.
last updated on 2024-08-23 18:31 CEST by the dblp team
all metadata released as open data under CC0 1.0 license
see also: Terms of Use | Privacy Policy | Imprint
dblp was originally created in 1993 at:
since 2018, dblp has been operated and maintained by:
the dblp computer science bibliography is funded and supported by: