William Raffe is a Research Fellow working on the ARC Linkage Project LP130100743. His research speciality is artificial intelligence in games, with a focus on adaptive personalized games.
William was awarded his PhD in Computer Science from RMIT in 2014 with a thesis titled “Personalized Procedural Map Generation in Games via Evolutionary Algorithms”. Before this, he graduated a Bachelor of Computer Science (Honours) from RMIT in 2009, majoring in Games, Graphics, and Digital Media. He has been a member of the Golden Key Honour Society since 2006 and has lectured, tutored, designed, and consulted on undergraduate games programming courses, capstone projects, and honours, masters, and PhD research projects since 2011.
Beyond researching adaptive artificial intelligence for personalizing games, William has also worked in the related research fields of cyber-physical game design, agent learning and control via reinforcement learning, recommendation systems via supervised learning, and a range of evolutionary computing topics. He has a passion for all forms of machine learning, computational intelligence, and metaheuristic optimization, as well as broader interests in many areas of data analytics and human-computer interaction.
William is a senior member of the RMIT Evolutionary Computing and Machine Learning (ECML) group, as well as an associated member of the RMIT Exertion Games Lab. He has published in and reviewed for a range of peer-reviewed conferences and journals regarding artificial intelligence in game and human-computer interaction, including TCIAIG, AIIDE, CIG, CEC, CHI, and CHI-Play.
- PhD in Computer Science, RMIT University, awarded 2014.
- Thesis title: “Personalized Procedural Map Generation in Games via Evolutionary Algorithms”.
- Bachelor of Computer Science (Honours), RMIT University, awarded 2009.
- Thesis title: “Virtual Asset Protection using View-based Similary Matching”.
- Bachelor of Computer Science, RMIT University, awarded 2008.
- Majoring in Games, Graphics, and Digital Media.
- Raffe, W.,Zambetta, F.,Li, X.,Kenneth, S. (2015). Integrated approach to personalized procedural map generation using evolutionary algorithms In: IEEE Transactions on Computational Intelligence and AI in Games, 7, 139 - 155
- Tamassia, M.,Zambetta, F.,Raffe, W.,Li, X. (2015). Learning options for an MDP from demonstrations In: Artificial Life and Computational Intelligence, Newcastle, Australia, 5-7 February 2015
- Ivanovic, J.,Raffe, W.,Zambetta, F.,Li, X. (2015). Combining Monte Carlo tree search and apprenticeship learning for capture the flag In: Proceedings of the Computational Intelligence and Games (IEEE CIG 2015), Tainan, Taiwan, 31 August - 2 September 2015
- Raffe, W.,Tamassia, M.,Zambetta, F.,Li, X.,Mueller, F. (2015). Enhancing theme park experiences through adaptive cyber-physical play In: Proceedings of the Computational Intelligence and Games (IEEE CIG 2015), Tainan, Taiwan, 31 August - 2 September 2015
- Raffe, W.,Zambetta, F.,Li, X. (2013). Neuroevolution of content layout in the PCG: Angry bots video game In: Proceedings of 2013 IEEE Congress on Evolutionary Computation, Canc�n, M�xico, 20-23 June 2013
- Raffe, W.,Zambetta, F.,Li, X. (2012). A survey of procedural terrain generation techniques using evolutionary algorithms In: Proceedings of the Congress of Evolutionary Computation (CEC 2012), Brisbane, Australia, 10-15 June 2012
- Raffe, W.,Zambetta, F.,Li, X. (2011). Evolving patch-based terrains for use in video games In: 13th Annual Genetic and Evolutionary Computation Conference (GECCO 2011), Dublin, Ireland, 12th - 16th July, 2011
1 PhD Current Supervisions