(SAIC: Science Applications International Corporation)
Abstract
Serious games are popular computer games that frequently simulate real-world events or processes designed for the purpose of solving a problem. Although they are often entertaining, their main purpose is to train or educate users. Not surprisingly, users exhibit different game play behaviors because of their diverse background and game experience. To improve the educational effectiveness of these games, it is important to understand and learn from the interaction between the users and the game engine. This paper presents a study attempting to apply machine learning techniques to the game log to discover: a) strategies that are common to players interacting with serious games and b) variances in the demographics of the player base for these strategies. This is an empirical study with end-user data while playing Missing, a serious game developed to help mitigate biases that people may exhibit when analyzing plausible hypothesis for observed events. We found a set of common strategies and interesting variances in player demographics associated with these strategies.
May 7, 2011 in CHI (Human Factors in Computing Systems)
#1Gifford Cheung(UW: University of Washington)H-Index: 5
#2Jeff Huang(UW: University of Washington)H-Index: 22
Video games are primarily designed for the players. However, video game spectating is also a popular activity, boosted by the rise of online video sites and major gaming tournaments. In this paper, we focus on the spectator, who is emerging as an important stakeholder in video games. Our study focuses on Starcraft, a popular real-time strategy game with millions of spectators and high level tournament play. We have collected over a hundred stories of the Starcraft spectator from online sources, ...
May 10, 2010 in AAMAS (Adaptive Agents and Multi-Agents Systems)
#1Jeff Orkin(MIT: Massachusetts Institute of Technology)H-Index: 12
#2Deb Roy(MIT: Massachusetts Institute of Technology)H-Index: 40
The Restaurant Game demonstrates an end-to-end system that captures and generates social behavior for virtual agents. Over 15,000 people have played The Restaurant Game, and we have developed a system to automatically learn patterns of interaction and dialogue from logs of their gameplay sessions. These patterns guide a case-based planning system, which generates behavior and dialogue for a virtual customer or waitress who can interact with a human, or with another agent. The Restaurant Game dem...
This paper presents CBRetaliate , an agent that combines Case-Based Reasoning (CBR) and Reinforcement Learning (RL) algorithms. Unlike most previous work where RL is used to improve accuracy in the action selection process, CBRetaliate uses CBR to allow RL to respond more quickly to changing conditions. CBRetaliate combines two key features: it uses a time window to compute similarity and stores and reuses complete Q-tables for continuous problem solving. We demonstrate CBRetaliate on a team-bas...
The introduction of a casino into a community, as evidenced from a large number of studies undertaken over the years in different parts of the globe, suggests that casino business affects the community's social and economic structure. This research considers the case of the introduction of a casino into Hamilton, a city in New Zealand with a population of approximately 129,000. Based on 945 responses, it is of particular note that differences in views regarding the casino were evident between th...
In this article, the culture and business of PC bangs in Korea are explored. Once just a convenient spot for high-speed connection, the PC bang has become a space for nurturing online gaming cultures. This article addresses two central characteristics of PC bang that have ensured its success. First, the paper explores the social and cultural dimensions of the PC bang as a space that nurtures the negotiation of offline and online relationships around online gaming cultures in Korea. Second, the p...
Last. Ashwin Ram(Georgia Institute of Technology)H-Index: 31
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The goal of transfer learning is to use the knowledge acquired in a set of source tasks to improve performance in a related but previously unseen target task. In this paper, we present a multilayered architecture named CAse-Based Reinforcement Learner (CARL). It uses a novel combination of Case-Based Reasoning (CBR) and Reinforcement Learning (RL) to achieve transfer while playing against the Game AI across a variety of scenarios in MadRTSTM, a commercial Real Time Strategy game. Our experiments...
This report discusses some issues concerning serious games, that is, (digital) games used for purposes other than mere entertainment. The starting point is the serious games concept itself, and wha ...
Our research investigates a case-based approach to plan recognition using incomplete incrementally learned plan libraries. To learn plan libraries, one must be able to process novel input. Retrieval based on similarities among concrete planning situations rather than among planning actions enables recognition despite the occurrence of newly observed planning actions and states. In addition, we explore the benefits of predictions using a measure that we call abstract similarity. Abstract similari...
Coverage includes- David "RM" Michael has been a successful independent software developer for over 10 years, working in a variety of industries, including video games. He is the owner of DavidRM Software (www.davidrm.com) and co-owner of Samu Games (www.samugames.com). Michael is the author of The Indie Game Development Survival Guide, and his articles about game design, development, and the game development industry have appeared on GameDev.net (www.gamedev.net) and in the book Game Design Per...
The video game market has become an established and ever-growing global industry. The health of the video and computer games industry, together with the variety of genres and technologies available, means that video game concepts and programmes are being applied in numerous different disciplines. One of these is the field known as serious games. The main goal of this paper is to collect all the relevant articles published during the last decade and create a trend analysis about the use of certai...
This paper describes a psychometrically-based approach to the measurement of collaborative problem solving skills, by mining and classifying behavioral data both in real-time and in post-game analyses. The data were collected from a sample of middle school children who interacted with a game-like, online simulation of collaborative problem solving tasks. In this simulation, a user is required to collaborate with a virtual agent to solve a series of tasks within a first-person maze environment. T...
#1Ben Samuel(UCSC: University of California, Santa Cruz)H-Index: 10
#2Josh McCoy(UCSC: University of California, Santa Cruz)H-Index: 7
Last. Noah Wardrip-Fruin(UCSC: University of California, Santa Cruz)H-Index: 22
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The non-linear nature of interactive narratives makes it difficult for authors of these systems to anticipate how players will interact with them. This paper presents the technique of story sampling for assisting in the authoring and evaluation of interactive narratives. An example of a potential application of story sampling is presented using data from the interactive narrative Prom Week, and authoring insights gained from this analysis are shared.