Publications

You can find most of my (academic) publications under my Google scholar profile.

[1]Michael Fairbank, Spyridon Samothrakis, and Luca Citi. Deep learning in target space. Journal of Machine Learning Research, 23:1--46, 2022.
[2]Damian Machlanski, Spyridon Samothrakis, and Paul Clarke. Undersmoothing causal estimators with generative trees. arXiv preprint arXiv:2203.08570, 2022.
[3]Spyridon Samothrakis. Artificial intelligence inspired methods for the allocation of common goods and services. Plos one, 16(9):e0257399, 2021.
[4]Yogesh K Dwivedi, Laurie Hughes, Elvira Ismagilova, Gert Aarts, Crispin Coombs, Tom Crick, Yanqing Duan, Rohita Dwivedi, John Edwards, Aled Eirug, et al. Artificial intelligence (ai): Multidisciplinary perspectives on emerging challenges, opportunities, and agenda for research, practice and policy. International Journal of Information Management, 57:101994, 2021.
[5]Husam Quteineh, Spyridon Samothrakis, and Richard Sutcliffe. Textual data augmentation for efficient active learning on tiny datasets. In Proceedings of the 2020 Conference on Empirical Methods in Natural Language Processing (EMNLP), pages 7400--7410. Association for Computational Linguistics, 2020.
[6]Daniel Hernandez, Kevin Denamganai, Sam Devlin, Spyridon Samothrakis, and James Alfred Walker. A comparison of self-play algorithms under a generalized framework. arXiv preprint arXiv:2006.04471, 2020.
[7]Spyridon Samothrakis. Open loop in natura economic planning. arXiv preprint arXiv:2005.01539, 2020.
[8]Christoph Salge, Emily Short, Mike Preuss, Spyridon Samothrakis, and Pieter Spronck. Applications of artificial intelligence in live action role-playing games (larp). In 2020 IEEE Conference on Games (CoG), pages 612--619. IEEE, 2020.
[9]Daniel Hernandez, Kevin Denamganaï, Yuan Gao, Peter York, Sam Devlin, Spyridon Samothrakis, and James Alfred Walker. A generalized framework for self-play training. In 2019 IEEE Conference on Games (CoG), pages 1--8. IEEE, 2019.
[10]Haider Raza and Spyridon Samothrakis. Bagging adversarial neural networks for domain adaptation in non-stationary eeg. In 2019 International Joint Conference on Neural Networks (IJCNN), pages 1--7. IEEE, 2019.
[11]Mohammed Alshahrani, Spyridon Samothrakis, and Maria Fasli. Identifying idealised vectors for emotion detection using cma-es. In Proceedings of the Genetic and Evolutionary Computation Conference Companion, pages 157--158, 2019.
[12]Spyridon Samothrakis, Diego Perez, and Simon Lucas. Training gradient boosting machines using curve-fitting and information-theoretic features for causal direction detection. In Cause Effect Pairs in Machine Learning, pages 331--338. Springer, Cham, 2019.
[13]David Thue, Mirjam Palosaari Eladhari, Joshua Allen McCoy, Mike Preuß, Spyridon Samothrakis, Emily Short, Anne Sullivan, Michael Treanor, and R Michael Young. Backstory generation. In Dagstuhl Reports, volume 7, pages 118--119. Schloss Dagstuhl Leibniz-Zentrum für Informatik GmbH, 2018.
[14]Spyridon Samothrakis. Kathryn e. merrick: Computational models of motivation for game-playing agents. Genetic Programming and Evolvable Machines, 19(4):567--568, 2018.
[15]Spyridon Samothrakis. artificial intelligence and labour. arXiv preprint arXiv:1803.06563, 2018.
[16]Mohammed Alshahrani, Spyridon Samothrakis, and Maria Fasli. Word mover's distance for affect detection. In 2017 International Conference on the Frontiers and Advances in Data Science (FADS), pages 18--23. IEEE, 2017.
[17]Tom Vodopivec, Spyridon Samothrakis, and Branko Ster. On monte carlo tree search and reinforcement learning. Journal of Artificial Intelligence Research, 60:881--936, 2017.
[18]Spyridon Samothrakis, Tom Vodopivec, Michael Fairbank, and Maria Fasli. Convolutional-match networks for question answering. In Proceedings of the Twenty-Sixth International Joint Conference on Artificial Intelligence, pages 2686--2692. International Joint Conferences on Artificial Intelligence, 2017.
[19]Spyridon Samothrakis, Maria Fasli, Diego Perez, and Simon Lucas. Default policies for global optimisation of noisy functions with severe noise. Journal of Global Optimization, 67(4):893--907, 2017.
[20]Diego Pérez-Liébana, Spyridon Samothrakis, Julian Togelius, Tom Schaul, and Simon M Lucas. Analyzing the robustness of general video game playing agents. In 2016 IEEE Conference on Computational Intelligence and Games (CIG), pages 1--8. IEEE, 2016.
[21]Spyridon Samothrakis. Narrative progression traits for role-playing games. Game and Puzzle Design, 2016.
[22]Spyridon Samothrakis, Tom Vodopivec, Maria Fasli, and Michael Fairbank. Match memory recurrent networks. In 2016 International Joint Conference on Neural Networks (IJCNN), pages 1339--1346. IEEE, 2016.
[23]Diego Perez-Liebana, Spyridon Samothrakis, Julian Togelius, Tom Schaul, and Simon M Lucas. General video game ai: Competition, challenges and opportunities. In Thirtieth AAAI conference on artificial intelligence, 2016.
[24]A Pavia, S Samothrakis, T Schaul, N Shaker, Moshe Sipper, J Togelius, G Yannakakis, and F Zambetta. Algorithms that learn to play like people. In Artificial and computational intelligence in games: Integration, pages 222--223. Schloss Dagstuhl-Leibniz-Zentrum fur Informatik GmbH, Dagstuhl Publishing, 2015.
[25]Spyridon Samothrakis and Maria Fasli. Emotional sentence annotation helps predict fiction genre. PloS one, 10(11):e0141922, 2015.
[26]Spyridon Samothrakis, Diego Perez-Liebana, Simon M Lucas, and Maria Fasli. Neuroevolution for general video game playing. In 2015 IEEE Conference on Computational Intelligence and Games (CIG), pages 200--207. IEEE, 2015.
[27]Diego Perez-Liebana, Spyridon Samothrakis, Julian Togelius, Tom Schaul, Simon M Lucas, Adrien Couëtoux, Jerry Lee, Chong-U Lim, and Tommy Thompson. The 2014 general video game playing competition. IEEE Transactions on Computational Intelligence and AI in Games, 8(3):229--243, 2015.
[28]D Perez, S Samothrakis, J Togelius, T Schaul, and S Lucas. Gvg-ai competition, 2014.
[29]Spyridon Samothrakis, Samuel A Roberts, Diego Perez, and Simon M Lucas. Rolling horizon methods for games with continuous states and actions. In 2014 IEEE Conference on Computational Intelligence and Games, pages 1--8. IEEE, 2014.
[30]Diego Perez, Sanaz Mostaghim, Spyridon Samothrakis, and Simon M Lucas. Multiobjective monte carlo tree search for real-time games. IEEE Transactions on Computational Intelligence and AI in Games, 7(4):347--360, 2014.
[31]Diego Perez, Spyridon Samothrakis, and Simon Lucas. Knowledge-based fast evolutionary mcts for general video game playing. In 2014 IEEE Conference on Computational Intelligence and Games, pages 1--8. IEEE, 2014.
[32]Spyridon Samothrakis, Diego Perez, Simon M Lucas, and Philipp Rohlfshagen. Predicting dominance rankings for score-based games. IEEE Transactions on Computational Intelligence and AI in Games, 8(1):1--12, 2014.
[33]Spyridon Samothrakis. Methods for tackling games of strict competition. PhD thesis, University of Essex, 2014.
[34]Diego Perez, Edward Powley, Daniel Whitehouse, Spyridon Samothrakis, Simon Lucas, and Peter I Cowling. The 2013 multi-objective physical travelling salesman problem competition. In 2014 IEEE Congress on Evolutionary Computation (CEC), pages 2314--2321. IEEE, 2014.
[35]Simon M Lucas, Spyridon Samothrakis, and Diego Perez. Fast evolutionary adaptation for monte carlo tree search. In European Conference on the Applications of Evolutionary Computation, pages 349--360. Springer, Berlin, Heidelberg, 2014.
[36]Diego Perez, Julian Togelius, Spyridon Samothrakis, Philipp Rohlfshagen, and Simon M Lucas. Automated map generation for the physical traveling salesman problem. IEEE Transactions on Evolutionary Computation, 18(5):708--720, 2013.
[37]Diego Perez, Spyridon Samothrakis, and Simon Lucas. Online and offline learning in multi-objective monte carlo tree search. In 2013 IEEE Conference on Computational Inteligence in Games (CIG), pages 1--8. IEEE, 2013.
[38]Diego Perez, Spyridon Samothrakis, Simon Lucas, and Philipp Rohlfshagen. Rolling horizon evolution versus tree search for navigation in single-player real-time games. In Proceedings of the 15th annual conference on Genetic and evolutionary computation, pages 351--358, 2013.
[39]Diego Perez, Edward J Powley, Daniel Whitehouse, Philipp Rohlfshagen, Spyridon Samothrakis, Peter I Cowling, and Simon M Lucas. Solving the physical traveling salesman problem: Tree search and macro actions. IEEE Transactions on Computational Intelligence and AI in Games, 6(1):31--45, 2013.
[40]Daniel Ashlock, Wendy Ashlock, Spyridon Samothrakis, Simon Lucas, and Colin Lee. From competition to cooperation: Co-evolution in a rewards continuum. In 2012 IEEE Conference on Computational Intelligence and Games (CIG), pages 33--40. IEEE, 2012.
[41]Karl Friston, Spyridon Samothrakis, and Read Montague. Active inference and agency: optimal control without cost functions. Biological cybernetics, 106(8):523--541, 2012.
[42]Spyridon Samothrakis, Simon Lucas, ThomasPhilip Runarsson, and David Robles. Coevolving game-playing agents: Measuring performance and intransitivities. IEEE Transactions on Evolutionary Computation, 17(2):213--226, 2012.
[43]Cameron B Browne, Edward Powley, Daniel Whitehouse, Simon M Lucas, Peter I Cowling, Philipp Rohlfshagen, Stephen Tavener, Diego Perez, Spyridon Samothrakis, and Simon Colton. A survey of monte carlo tree search methods. IEEE Transactions on Computational Intelligence and AI in games, 4(1):1--43, 2012.
[44]Spyridon Samothrakis and Simon Lucas. Approximating n-player behavioural strategy nash equilibria using coevolution. In Proceedings of the 13th annual conference on Genetic and evolutionary computation, pages 1107--1114, 2011.
[45]Spyridon Samothrakis, David Robles, and Simon Lucas. Fast approximate max-n monte carlo tree search for ms pac-man. IEEE Transactions on Computational Intelligence and AI in Games, 3(2):142--154, 2011.
[46]Spyridon Samothrakis and Simon M Lucas. Planning using online evolutionary overfitting. In 2010 UK Workshop on Computational Intelligence (UKCI), pages 1--6. IEEE, 2010.
[47]Spyridon Samothrakis, David Robles, and Simon M Lucas. A uct agent for tron: Initial investigations. In Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games, pages 365--371. IEEE, 2010.

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