| Issue Date | Title | Author(s) |
| 2019-01-29 | Challenging AI: Evaluating the Effect of MCTS-Driven Dynamic Difficulty Adjustment on Player Enjoyment | Demediuk, S; Tamassia, M; Li, X; Raffe, WL |
| 2016-01-01 | Dynamic choice of state abstraction in Q-learning | Tamassia, M; Zambetta, F; Raffe, WL; Mueller, FF; Li, X |
| 2015-11-04 | Enhancing theme park experiences through adaptive cyber-physical play | Raffe, WL; Tamassia, M; Zambetta, F; Li, X; Mueller, FF |
| 2015-01-01 | Learning options for an MDP from demonstrations | Tamassia, M; Zambetta, F; Raffe, W; Li, X |
| 2018-03-01 | Learning Options From Demonstrations: A Pac-Man Case Study | Tamassia, M; Zambetta, F; Raffe, WL; Mueller, FF; Li, X |
| 2018-01-29 | Measuring player skill using dynamic difficulty adjustment | Demediuk, S; Tamassia, M; Raffe, WL; Zambetta, F; Mueller, FF; Li, X |
| 2017-10-23 | Monte Carlo tree search based algorithms for dynamic difficulty adjustment | Demediuk, S; Tamassia, M; Raffe, WL; Zambetta, F; Li, X; Mueller, F |
| 2018-01-29 | Player retention in league of legends: A study using survival analysis | Demediuk, S; Murrin, A; Bulger, D; Hitchens, M; Drachen, A; Raffe, WL; Tamassia, M |
| 2015-10-05 | Player-computer interaction features for designing digital play experiences across six degrees of water contact | Raffe, WL; Tamassia, M; Zambetta, F; Li, X; Pell, SJ; Mueller, FF |
| 2016-07-02 | Predicting player churn in destiny: A Hidden Markov models approach to predicting player departure in a major online game | Tamassia, M; Raffe, W; Sifa, R; Drachen, A; Zambetta, F; Hitchens, M |
| 2020-01-22 | Reducing perceived waiting time in theme park queues via an augmented reality game | Zambetta, F; Raffe, W; Tamassia, M; Mueller, FF; Li, X; Quinten, N; Patibanda, R; Dang, D; Satterley, J |
