An inclusive view of player modeling

Smith, Adam M.; Lewis, Cynthia; Hullet, Kenneth; Smith, Gillian; Sullivan, Anne

doi:10.1145/2159365.2159419

Cited by 74 publications

(61 citation statements)

References 5 publications

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“…Smith et al [37] provide a very broad view of player modeling and apart from the source of the data, they also categorize player modeling methods according to three other facets. These are scope (individual, class, universal and hypothetical), purpose (generative and descriptive) and domain (human actions and game reactions).…”

Section: Player Modeling and Game Data Miningmentioning

confidence: 99%

Give me a reason to dig Minecraft and psychology of motivation

Canossa

Martinez²,

Togelius

2013

2013 IEEE Conference on Computational Inteligence in Games (CIG)

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Abstract-Recently, both game industry professionals and academic researchers have started focusing on playergenerated behavioral data as a mean to gather insights on player psychology through datamining. Although some research has already proven solid correlations between ingame behavior and personality, most techniques focus on extracting knowledge from in-game behavior data alone. This paper posits that triangulating exclusively behavioral datasets with established theoretical frameworks serving as hermeneutic grids, may help extracting additional meaning and information. The hermeneutic grid selected for this study is the Reiss Motivation Profiler and it is applied to behavioral data gathered from Minecraft players.

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Section: Player Modeling and Game Data Miningmentioning

confidence: 99%

Give me a reason to dig Minecraft and psychology of motivation

Canossa

Martinez²,

Togelius

2013

2013 IEEE Conference on Computational Inteligence in Games (CIG)

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“…However, the term player modeling lacks a clear definition, resulting in different authors providing different definitions [17]. We adhere to a general definition that player modeling is a field of AI that focuses on understanding and modeling the characteristics of a player.…”

Section: Introductionmentioning

confidence: 99%

Play style: Showing your age

Tekofsky

Spronck

Plaat

et al. 2013

2013 IEEE Conference on Computational Inteligence in Games (CIG)

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Abstract-Age has been shown to influence our preferences, choices, and cognitive performance. We expect this influence to be visible in the play style of an individual. Player models would then benefit from incorporating age, allowing developers to offer an increasingly personalized game experience to the player. To investigate the relationship between age and play style, we set out to determine how much of the variance in a player's age can be explained by his play style. For this purpose, we used the data from a survey ('PsyOps') among 13,376 'Battlefield 3' players. Starting out with 60 play style variables, we found that 45.7% of the variance in age can be explained by 46 play style variables. Furthermore, similar percentages of variance in age are explained when the sample is divided along gaming platform: 31 play style variables explain 43.1% on PC; 30 play style variables explain 53.9% on Xbox 360; 28 play style variables explain 51.7% on Playstation 3. Our findings have a high external validity due to the large and heterogeneous nature of the sample. The strength of the relationship between age and play style is considered 'large' according to Cohen's classification. Previous research indicates that the nature of the relationship between age and play style is likely to be based on life-time developments in cognitive performance, motivation, and personality. All in all, our findings merit a recommendation to incorporate age in future player models.

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“…Picard [4] has based on emotional communication (frustration, confusion, disliking, interest…) to design player model. Smith et al [4,5] introduce a classification of player modeling.…”

Section: A Player Modelingmentioning

confidence: 99%

“…Smith et al [4,5] introduce a classification of player modeling. They define a player model using the four dimensions scope of application, purpose of use, domain of modeled details, and source of model's derivation or motivation.…”

Section: A Player Modelingmentioning

confidence: 99%

Simulation for Collaborative Serious Game Using Player’s Modeling and Agent Technology

2016

IJCCIE

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Abstract-The concept of multiplayer serious games that support collaborative learning offers advantages and opportunities. It can add a social part to the process of gaming, stressing the role of interaction between players, affecting social skills like teamwork or communication and competence skills.Players have different preferences and styles of gaming. Current approaches to adapt game make it possible for different elements to adjust to the player. However most of these approaches can adapt one single player; so we need to find ways to aggregate all users input and history into some potential information that can be used for the adaptation mechanism. Based on player's modeling and agent technology, A model to simulate collaborative multiplayer serious games has proposed in this paper.

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An inclusive view of player modeling

Cited by 74 publications

References 5 publications

Give me a reason to dig Minecraft and psychology of motivation

Give me a reason to dig Minecraft and psychology of motivation

Play style: Showing your age

Simulation for Collaborative Serious Game Using Player’s Modeling and Agent Technology

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