World's Best Scientists 2026 revealed!

D-Index & Metrics

Computer Science

D-Index
40
Citations
11166
World Ranking
9079
National Ranking
559

Overview

Peter I. Cowling is affiliated with Queen Mary University of London in the United Kingdom. Their research spans multiple fields, including Social Sciences, Computer Science, and Neuroscience.

The scientist's main subfields of study encompass Safety Research, Cognitive Neuroscience, Sociology and Political Science, Health Informatics, and Human-Computer Interaction. Their research has focused on topics related to Ethics and Social Impacts of AI, Innovation, Sustainability and Human-Machine Systems, Artificial Intelligence in Healthcare and Education, Neuroethics, Human Enhancement and Biomedical Innovations, Innovative Human-Technology Interaction, Music and Audio Processing, and Neuroscience and Music Perception.

Peter I. Cowling has published primarily in the venue AI & Society, contributing to two papers there. The recent publications include:

  • "Speeding up to keep up: exploring the use of AI in the research process" (2021, AI & Society)
  • "Expert views about missing AI narratives: is there an AI story crisis?" (2022, AI & Society)

These papers explore themes around the role and impact of artificial intelligence within research frameworks and societal narratives.

Frequent collaborators in Cowling's research efforts include Jennifer Chubb, Darren Reed, Duncan Williams, and Damian Murphy.

Best Publications

  • A Survey of Monte Carlo Tree Search Methods

    C. B. Browne;E. Powley;D. Whitehouse;S. M. Lucas

  • A hyperheuristic approach to scheduling a sales summit

    Peter Cowling;Graham Kendall;Eric Soubeiga

  • Using real time information for effective dynamic scheduling

    Peter I. Cowling;Marcus Johansson

  • A Memetic Approach to the Nurse Rostering Problem

    Edmund Burke;Peter Cowling;Patrick De Causmaecker;Greet Vanden Berghe

  • MMAC: a new multi-class, multi-label associative classification approach

    F.A. Thabtah;P. Cowling;Yonghong Peng

  • MCAR: multi-class classification based on association rule

    F. Thabtah;P. Cowling;Y. Peng

  • Hyperheuristics: Recent Developments

    Konstantin Chakhlevitch;Peter I. Cowling

  • Information Set Monte Carlo Tree Search

    P. I. Cowling;E. J. Powley;D. Whitehouse

  • An investigation of a hyperheuristic genetic algorithm applied to a trainer scheduling problem

    P. Cowling;G. Kendall;Limin Han

  • Fuzzy grey relational analysis for software effort estimation

    Mohammad Azzeh;Daniel Neagu;Peter I. Cowling

  • Hyperheuristics: A Tool for Rapid Prototyping in Scheduling and Optimisation

    Peter I. Cowling;Graham Kendall;Eric Soubeiga

  • A multi-agent architecture for dynamic scheduling of steel hot rolling

    Peter I. Cowling;Djamila Ouelhadj;Sanja Petrovic

  • A flexible decision support system for steel hot rolling mill scheduling

    Peter Cowling

  • From value chains to technological platforms: The effects of crowdfunding in the digital game industry

    Alberto Nucciarelli;Alberto Nucciarelli;Feng Li;Kiran Jude Fernandes;Nikolaos Goumagias

  • Dynamic scheduling of steel casting and milling using multi-agents

    Peter I. Cowling;D. Ouelhadj;S. Petrovic

  • Integration of continuous caster and hot strip mill planning for steel production

    Peter Cowling;Wafa Rezig

  • A Parameter-Free Hyperheuristic for Scheduling a Sales Summit

    Peter Cowling;Graham Kendall;Eric Soubeiga

  • Ensemble Determinization in Monte Carlo Tree Search for the Imperfect Information Card Game Magic: The Gathering

    P. I. Cowling;C. D. Ward;E. J. Powley

  • Analogy-based software effort estimation using Fuzzy numbers

    Mohammad Azzeh;Daniel Neagu;Peter I. Cowling

  • Win Prediction in Multi-Player Esports: Live Professional Match Prediction

    Victoria J. Hodge;Sam Michael Devlin;Nicholas John Sephton;Florian Oliver Block

  • Multiple labels associative classification

    Abdeljaber Thabtah;Peter Cowling;Yonghong Peng

  • Production, Manufacturing and Logistics Using real time information for effective dynamic scheduling

    Peter Cowling;Marcus Johansson

Frequent Co-Authors

Keshav Dahal
Keshav Dahal University of the West of Scotland
Graham Kendall
Graham Kendall MILA University
Edmund K. Burke
Edmund K. Burke Bangor University
Fadi Thabtah
Fadi Thabtah Manukau Institute of Technology
Anders Drachen
Anders Drachen University of Southern Denmark
Sanja Petrovic
Sanja Petrovic University of Nottingham
Simon M. Lucas
Simon M. Lucas Queen Mary University of London
Alberto Caprara
Alberto Caprara University of Bologna
David Pisinger
David Pisinger Technical University of Denmark

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