Michael Kirley

Reproducibility and baseline reporting for dynamic multi-objective benchmark problems

D Herring, M Kirley, X Yao

Conference Proceedings  |  2022  |  GECCO 2022 - Proceedings of the 2022 Genetic and Evolutionary Computation Conference

Dynamic multi-objective optimization problems (DMOPs) are widely accepted to be more challenging than stationary problems due to t..

Can machine learning improve small area population forecasts? A forecast combination approach

Irina Grossman, Kasun Bandara, Tom Wilson, Michael Kirley

Journal article  |  2022  |  COMPUTERS ENVIRONMENT AND URBAN SYSTEMS

Generating accurate small area population forecasts is vital for governments and businesses as it provides better grounds for deci..

Boosting ant colony optimization via solution prediction and machine learning

Yuan Sun, Sheng Wang, Yunzhuang Shen, Xiaodong Li, Andreas T Ernst, Michael Kirley

Journal article  |  2022  |  COMPUTERS & OPERATIONS RESEARCH

This paper introduces an enhanced meta-heuristic (ML-ACO) that combines machine learning (ML) and ant colony optimization (ACO) to..

Study of Planetary Boundary Layer, Air Pollution, Air Quality Models and Aerosol Transport Using Ceilometers in New South Wales (NSW), Australia

Nguyen Duc Hiep, Md Mahmudur Rahman, Toan Trieu, Merched Azzi, Matthew Riley, Thomas Koh, Shaohua Liu, Kasun Bandara, Vishall Krishnan, Yujing Yang, Jeremy Silver, Michael Kirley, Stephen White, Jordan Capnerhurst, John Kirkwood

Journal article  |  2022  |  ATMOSPHERE

The planetary boundary layer height (PBLH) is one of the key factors in influencing the dispersion of the air pollutants in the tr..

Analysing Multiobjective Optimization Using Evolutionary Path Length Correlation

D Herring, D Pakravan, M Kirley

Conference Proceedings  |  2022  |  Lecture Notes in Computer Science (including subseries Lecture Notes in Artificial Intelligence and Lecture Notes in Bioinformatics)

Recently, a number of studies have attempted to characterize the interaction between objectives and decision variables in multiobj..

An Instance Space Analysis of Constrained Multi-Objective Optimization Problems

H Alsouly, M Kirley, MA Munoz

Journal article  |  2022  |  IEEE Transactions on Evolutionary Computation

Constrained multi-objective optimization problems (CMOPs) are generally more challenging than unconstrained problems. This in part..

Analyzing randomness effects on the reliability of exploratory landscape analysis

Mario Andres Munoz, Michael Kirley, Kate Smith-Miles

Journal article  |  2021  |  NATURAL COMPUTING

The inherent difficulty of solving a continuous, static, bound-constrained and single-objective black-box optimization problem dep..

Sampling Effects on Algorithm Selection for Continuous Black-Box Optimization

Mario Andres Munoz, Michael Kirley

Journal article  |  2021  |  ALGORITHMS

In this paper, we investigate how systemic errors due to random sampling impact on automated algorithm selection for bound-constra..

The Role of Environments in Affording Deceptive Behaviour: Some Preliminary Insights from Stage Magic

W Smith, M Kirley, L Sonenberg, F Dignum

Book Chapter  |  2021  |  Communications in Computer and Information Science

Drawing on an ecological perspective, we contend that research into deception in AI needs to consider not only the cognitive struc..

Extended Goal Recognition: Lessons from Magic

Peta Masters, Wally Smith, Michael Kirley

Journal article  |  2021  |  FRONTIERS IN ARTIFICIAL INTELLIGENCE

The "science of magic" has lately emerged as a new field of study, providing valuable insights into the nature of human perception..