Dr John Levine

Senior Teaching Fellow

Computer and Information Sciences

Publications

On skipping behaviour types in music streaming sessions
Meggetto Francesco, Revie Crawford, Levine John, Moshfeghi Yashar
CIKM '21 International Conference on Information and Knowledge Management, Proceedings, pp. 3333-3337 (2021)
https://doi.org/10.1145/3459637.3482123
A continuous information gain measure to find the most discriminatory problems for AI benchmarking
Stephenson Matthew, Anderson Damien, Khalifa Ahmed, Levine John, Renz Jochen, Togelius Julian, Salge Christoph
2020 IEEE Congress on Evolutionary Computation, CEC 2020 - Conference Proceedings 2020 IEEE Congress on Evolutionary Computation, CEC 2020 (2020)
https://doi.org/10.1109/CEC48606.2020.9185834
Ensemble Decision Systems for general video game playing
Anderson Damien, Rodgers Philip, Levine John, Guerrero-Romero Cristina, Perez-Liebana Diego
IEEE Conference on Games (COG) 2019 (2019)
Open-world games : an exploration of creative play
Arnott Lorna, Levine John, Shanks Gillian
Early Learning in the Digital Age (2019) (2019)
Ensemble decision making in real-time games
Rodgers Philip, Levine John, Anderson Damien
2018 IEEE Conference on Computational Intelligence and Games (CIG) 2018 IEEE Conference on Computational Intelligence and Games (2018)
https://doi.org/10.1109/CIG.2018.8490401
Deceptive games
Anderson Damien, Stephenson Matthew, Togelius Julian, Salge Christian, Levine John, Renz Jochen
, pp. 376-391 (2018)
https://doi.org/10.1007/978-3-319-77538-8_26

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Professional activities

IEEE Congress on Evolutionary Computation
Member of programme committee
2011
EPSRC (Engineering and Physical Sciences Research Council) (External organisation)
Member
2010
EPSRC (Engineering and Physical Sciences Research Council) (External organisation)
Member
2008
International Journal of Metaheuristics (Journal)
Editorial board member
1/2008

More professional activities

Projects

Capita PhD Studentship Application Awarded: Open World Gaming for Young Children's Creative Play
Arnott, Lorna (Academic) Levine, John (Academic)
01-Jan-2015 - 01-Jan-2019
EVOLVING AND GENERALISING VERY HIGH QUALITY KNOWLEDGE FOR AI PLANNING
Levine, John (Principal Investigator) Fox, Maria (Co-investigator) Long, Derek (Co-investigator)
This project is concerned with making AI planning practical by exploiting evolutionary learning techniques to acquire control knowledge automatically. This control knowledge can be used to prune useless branches of the search space and to propose promising branches. Whilst human-coded control rules have been shown to be useful in planning, their specification is an effort-intensive process which makes them difficult or impossible to generalise. Their use has tended to be confined to relatively simple domain models about which the human has a good understanding of the dynamics. We propose to learn powerful rules automatically from both static and dynamic sources of information about the planning domain and the process of planning within that domain. Furthermore, we will develop a method for learning generic rules that apply to classes of domains and that can be automatically customised for a particular domain. This reduces or even removes the burden on the human and results in scalable planning technology.
01-Jan-2006 - 31-Jan-2010

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Address

Computer and Information Sciences
Livingstone Tower

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