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Combining modeling and gaming for predictive analytics

Roderick M Riensche, Paul D Whitney
2012 Security Informatics  
In this paper we describe our approach of combining modeling and gaming disciplines to develop predictive capabilities, using formal models to inform game development, and using games to provide data for  ...  The resulting predictive capability combines human expertise and actions with computational modeling capabilities, resulting in a predictive capability that may approach the richness and diversity of human  ...  Paul Whitney led the projects relating to computational modeling. Rick Riensche led the projects related to analytical gaming. This work has been supported by the Technosocial Predictive  ... 
doi:10.1186/2190-8532-1-11 fatcat:wh2ktbcahbd5nmrwr2dbwbzlia

Comprehensive review and classification of game analytics

Yanhui Su, Per Backlund, Henrik Engström
2020 Service Oriented Computing and Applications  
Fourth, we also list different algorithms that have been used in game analytics for prediction.  ...  Based on the categories established after the mapping and the review findings, we also discuss the limitations of game analytics and propose potential research points for future research.  ...  Acknowledgements This research was supported by the University of Skövde, Sweden Game Arena and the Game Hub Scandinavia 2.0 (NYPS 20201849) project under the EU regional development fund Interreg Öresund-Kattegat-Skagerrak  ... 
doi:10.1007/s11761-020-00303-z fatcat:6el2vmkwpvfzhkgrosfdpjimni

Game Plan: What AI can do for Football, and What Football can do for AI [article]

Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steele, Pauline Luc, Adria Recasens (+24 others)
2020 arXiv   pre-print
We review the state-of-the-art and exemplify the types of analysis enabled by combining the aforementioned fields, including illustrative examples of counterfactual analysis using predictive models, and  ...  The research challenges associated with predictive and prescriptive football analytics require new developments and progress at the intersection of statistical learning, game theory, and computer vision  ...  Acknowledgments The authors gratefully thank Thomas Anthony and Murray Shanahan for their helpful feedback during the paper writing process.  ... 
arXiv:2011.09192v1 fatcat:wydr55wiz5h6lhuhhjajho4k3i

Spatial game analytics and visualization

Anders Drachen, Matthias Schubert
2013 2013 IEEE Conference on Computational Inteligence in Games (CIG)  
We summarize the current problems and challenges in the field, and present four key areas of spatial and spatio-temporal analytics: Spatial Outlier Detection, Spatial Clustering, Spatial Predictive Models  ...  The recently emerged field of game analytics and the development and adaptation of business intelligence techniques to support game design and development has given data-driven techniques a direct role  ...  Common methods for spatial prediction include Markov random fields [14, 22] and spatial autoregressive models [22] .  ... 
doi:10.1109/cig.2013.6633629 dblp:conf/cig/DrachenS13 fatcat:r2yiiux2ojgp3khn2li7trag54

Game Plan: What AI can do for Football, and What Football can do for AI

Karl Tuyls, Shayegan Omidshafiei, Paul Muller, Zhe Wang, Jerome Connor, Daniel Hennes, Ian Graham, William Spearman, Tim Waskett, Dafydd Steel, Pauline Luc, Adria Recasens (+24 others)
2021 The Journal of Artificial Intelligence Research  
We review the state-of-the-art and exemplify the types of analysis enabled by combining the aforementioned fields, including illustrative examples of counterfactual analysis using predictive models, and  ...  The research challenges associated with predictive and prescriptive football analytics require new developments and progress at the intersection of statistical learning, game theory, and computer vision  ...  Acknowledgments The authors gratefully thank Thomas Anthony and Murray Shanahan for their helpful feedback during the paper writing process.  ... 
doi:10.1613/jair.1.12505 fatcat:klaw7alkzrhp7kd7ebdefpxh7e

Data Science Approach to predict the winning Fantasy Cricket Team Dream 11 Fantasy Sports [article]

Sachin Kumar S, Prithvi HV, C Nandini
2022 arXiv   pre-print
We built a predictive model that predicts the performance of players in a prospective game.  ...  You either win big, win small, or lose your bet based on the performance of the players selected for your fantasy team in the prospective game, and our model increases the probability of you winning big  ...  for the team and the game itself.  ... 
arXiv:2209.06999v1 fatcat:rk3ncvqvhbdlvpczywh3fb2sje

A comparison of two analytical evaluation methods for educational computer games for young children

Mathilde M. Bekker, Ester Baauw, Wolmet Barendregt
2007 Cognition, Technology & Work  
In this paper we describe a comparison of two analytical methods for educational computer games for young children.  ...  Malone and Lepper) with both usability and fun heuristics for children's computer games.  ...  We also thank Arnold Vermeeren from the Technical University of Delft (the Netherlands) for his useful comments on an earlier version of this paper.  ... 
doi:10.1007/s10111-007-0068-x fatcat:hl4q6rjfmzhirllvpznp7nbnfa

To be or not to be...social

Anders Drachen, Mari Pastor, Aron Liu, Dylan Jack Fontaine, Yuan Chang, Julian Runge, Rafet Sifa, Diego Klabjan
2018 Proceedings of the Australasian Computer Science Week Multiconference on - ACSW '18  
interactions typical of casual mobile games, on predictions of premium users and Customer Lifetime Value by applying classi ers and regression models respectively.  ...  As only a small fraction of users make purchases, predicting these users and their Customer Lifetime Value are key challenges in Game Analytics and currently barely explored in academic research.  ...  and C5.0 [20] algorithms. e use of multiple classi ers is common in game analytics and behavioral prediction in general for identifying the best models for a speci c task [14, 23, 26] .  ... 
doi:10.1145/3167918.3167925 dblp:conf/acsw/DrachenPLFCRSK18 fatcat:kn6dpc6lenfxvksoxg7yqr3rla

Data-driven Model for Mobile Game Self-publishing

Yanhui Su
2019 Business Informatics Research  
This new model combines user behavior data with in-game system analysis effectively.  ...  model for mobile game self-publishing, primarily targeting independent (indie) game developers.  ...  They rarely rise to the analytics angle and provide statistical analysis, forecasting, prediction, and optimization suggestions. As for the mobile game analytics, Drachen et al.  ... 
dblp:conf/bir/Su19 fatcat:a6ypiqpz3jerrkkzo2hpnezrgu

Game Theory and an Improved Maximum Entropy-Attribute Measure Interval Model for Predicting Rockburst Intensity

Yakun Zhao, Jianhong Chen, Shan Yang, Zhe Liu
2022 Mathematics  
On the one hand, the reasonableness of the combined weights of indexes was analyzed; on the other hand, the results of this paper's model were compared with the three analytical models for predicting rockburst  ...  Moreover, in order to balance the shortcomings of the subjective weights of the Analytic Hierarchy Process and the objective weights of the CRITIC method, game theory was used for the combined weights,  ...  Since these methods are well suited for predicting rockburst, game theory and an improved maximum entropyattribute measurement interval model were proposed for predicting rockburst intensity in this paper  ... 
doi:10.3390/math10152551 fatcat:pt6tino6fjdaxcl6valqixyocm

Social Media Predictive Analytics

Svitlana Volkova, Benjamin Van Durme, David Yarowsky, Yoram Bachrach
2015 Proceedings of the 2015 Conference of the North American Chapter of the Association for Computational Linguistics: Tutorial Abstracts  
We will start with an overview of the existing approaches for social media predictive analytics. We will describe the state-of-the-art static (batch) models and features.  ...  We will then present models for streaming (online) inference from single and multiple data streams; and formulate a latent attribute prediction task as a sequence-labeling problem.  ...  She works on machine learning and natural language processing techniques for social media predictive analytics.  ... 
doi:10.3115/v1/n15-4005 dblp:conf/naacl/VolkovaDYB15 fatcat:4t2f7rdy65cexnf5h3vjmvr3g4

Technosocial predictive analytics for security informatics

Antonio Sanfilippo, Nigel Gilbert, Mark Greaves
2012 Security Informatics  
The approach relies on the use of formal models to inform game development, and the use of gaming techniques to generate data for modeling.  ...  Roderick Riensche and Paul Whitney describe an approach to fostering collaborative decision-making based on the combination of modeling and gaming methodologies and capabilities.  ... 
doi:10.1186/2190-8532-1-8 fatcat:suittmhr4zdotdq6i6w7cffiti

Comparison of Off the Shelf Data Mining Methodologies in Educational Game Analytics

David J. Gagnon, Erik Harpstead, Stefan Slater
2019 Educational Data Mining  
The games being studied, the Crystal Cave and Wave Combinator, are both short duration (played for an average of 25 and 28 minutes respectfully), web-based games designed for use in classroom contexts.  ...  We found that logistic regression produced the best models overall and model quality was influenced by specific game levels and assessment items.  ...  Individual models were generated for quitting at levels 1, 3, 5 and 7 for each game.  ... 
dblp:conf/edm/GagnonHS19 fatcat:o56maqj3lbfvpbozjjd7gke6zq

Towards a New Platform Based on Learning Outcomes Analysis For Mobile Serious Games

Lotfi Elaachak
2020 International Journal of Emerging Technologies in Learning (iJET)  
This ability can be measured and then analyzed by using several techniques and algorithms like learning analytics, educational data mining, inference knowledge e.g. "Bayesian Knowledge Tracing", etc.  ...  There are now a large number of both instructional applications and mobile serious games "MSGs" which are available in mobile applications stores.  ...  will be class for the predictive and inference knowledge models, see Figure 8 .  ... 
doi:10.3991/ijet.v15i02.11637 fatcat:haavwxvusbaufbz2z32pfjzire

What Do Agent-Based and Equation-Based Modelling Tell Us About Social Conventions: The Clash Between ABM and EBM in a Congestion Game Framework

Federico Cecconi, Marco Campenni, Giulia Andrighetto, Rosaria Conte
2010 Journal of Artificial Societies and Social Simulation  
We call parallel the directions North-South and South-North, and the directions West-East and East-West. We define orthogonal the other combinations.  ...  We consider a game where each individual follows one out of four behaviors, WatchRight, WatchLeft, Dove and Hawk. We denote the behavior with the index I.  ...  The results generated by the simulations may fit the analytical model: they provide in silico data for developing the analytical model to generalize the simulation results and to make predictions (Conte  ... 
doi:10.18564/jasss.1585 fatcat:4jhkdz54gvcxvkb6svrto4xedy
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