A5013771792- Artificial Intelligence in Games
- Digital Games and Media
- Gambling Behavior and Treatments
- Sports Analytics and Performance
- Sport Psychology and Performance
- Educational Games and Gamification
- Flow Experience in Various Fields
- Second Language Acquisition and Learning
- Computer Graphics and Visualization Techniques
- Data Mining Algorithms and Applications
- Sports Performance and Training
- Video Analysis and Summarization
- Reinforcement Learning in Robotics
- EFL/ESL Teaching and Learning
- Time Series Analysis and Forecasting
University of York
2014-2023
Esports are competitive videogames watched by audiences. Most esports generate detailed data for each match that publicly available. analytics research is focused on predicting outcomes. Previous has emphasized prematch prediction and used from amateur games, which more easily available than those professional level. However, the commercial value of win exists at Furthermore, real-time unexplored, as its potential informing Here, we present first comprehensive case study live in a esport. We...
Esports - video games played competitively that are broadcast to large audiences a rapidly growing new form of mainstream entertainment. borrow from traditional TV, but qualitatively different genre, due the high flexibility content capture and availability detailed gameplay data. Indeed, in esports, there is access both real-time historical data about any action taken virtual world. This aspect motivates research presented here, question asked being: can information buried deep such data,...
Abstract Within limited‐input language classrooms, understanding the effect of distribution practice (spacing between practice) on learning is critical, yet evidence conflicting and limited relevance for young learners. For second (L2) grammar learning, some studies reveal advantages spacing 7 days or more, but others shorter spacing. Further, little known about role cognitive individual differences (e.g., analytic ability; LAA) in mediating effects L2 grammatical knowledge development...
Monte Carlo Tree Search (MCTS) has become a popular solution for controlling non-player characters. Its use repeatedly been shown to be capable of creating strong game playing opponents. However, the emergent playstyle agents using MCTS is not necessarily human-like, believable or enjoyable. AI Factory Spades, currently top rated Spades in Google Play store, uses variant control In collaboration with developers, we collected gameplay data from 27,592 games and showed previous study that...
Esports has emerged as a popular genre for players well spectators, supporting global entertainment industry. analytics evolved to address the requirement data-driven feedback, and is focused on cyber-athlete evaluation, strategy prediction. Towards latter, previous work used match data from variety of player ranks hobbyist professional players. However, have been shown behave differently than lower ranked Given comparatively limited supply data, key question thus whether mixed-rank datasets...
Move pruning is a technique used in game tree search which incorporates heuristic knowledge to reduce the number of moves under consideration from particular state. This paper investigates Heuristic Pruning on strategic card Lords War. We use heuristics guide our and experiment with different techniques applying their relative effectiveness. also present artificially rolling forward state an attempt more accurately determine are appropriate prune decision tree. demonstrate that move...
How does the difficulty of a task affect people's enjoyment and engagement? Intrinsic motivation flow theories posit ‘goldilocks’ optimum where matches performer skill, yet current work is confounded by questionable measurement practices lacks scalable methods to manipulate objective difficulty-skill ratios. We developed two-player tactical game test suite with an artificial intelligence (AI)-controlled opponent that uses variant Monte Carlo Tree Search algorithm precisely A pre-registered...
The final step in the Monte Carlo Tree Search algorithm is to select action play from root level of tree. Experimentation on modifying selection mechanism has been somewhat limited date, particularly with respect consider aspects other than playing strength. This paper investigates modification as an attempt produce a more entertaining opponent strategic card game Lords War. These mechanisms are played against our most effective Information Set MCTS agent, and we investigate their...
In this paper, we analyze the gameplay data of three popular customizable card games where players build decks prior to gameplay. We from a player engagement perspective, how business model affects players, influence and provide strategic insights for themselves. Sifa et al. found lack cross-game analytics, whereas Marchand Hennig-Thurau identified understanding game's strategies affect players. address both issues. The have similar models but differ in one aspect: distribution cards used...
Process parallelization is more important than ever, as most modern hardware contains multiple processors and advanced multi-threading capability. This paper presents an analysis of the parallel behaviour Information Set Monte Carlo Tree Search Upper Confidence Bounds for Trees (UCT) variant MCTS, certain techniques (specifically Parallelization) have different effects upon ISM-CTS Plain UCT. The a study relative effectiveness types parallelization, including Root, Tree, with Virtual Loss, Leaf.
How does the difficulty of a task affect people’s enjoyment and engagement? Intrinsic motivation flow theories posit ‘goldilocks’ optimum where matches performer skill, yet current work is confounded by questionable measurement practices lacks scalable methods to manipulate objective difficulty-skill ratios. We developed 2-player tactical game test suite with an AI-controlled opponent that uses variant Monte Carlo Tree Search algorithm precisely A pre-registered study (n=311) showed our AI...
As part of their design, card games often include information that is hidden from opponents and represents a strategic advantage if discovered. A player can discover this will be able to alter strategy based on the nature information, therefore become more competent opponent. In paper, we employ association rule-mining techniques for predicting item multisets, show them effective in content Netrunner decks. We then apply different modifications heuristic knowledge game, effectiveness which...