An activity theory-based model for serious games analysis and conceptual design

There are currently a number of models, frameworks and methodologies for serious games analysis and design that provide useful interpretations of the possibilities and limitations offered by serious games. However, these tools focus mostly on high-level aspects and requirements and do not help understand how such high-level requirements can be concretely satisfied. In this paper, we present a conceptual model, called Activity Theory-based Model of Serious Games (ATMSG), that aims to fill this gap. ATMSG supports a systematic and detailed representation of educational serious games, depicting the ways that game elements are connected to each other throughout the game, and how these elements contribute to the achievement of the desired pedagogical goals. Three evaluation studies indicate that ATMSG helped participants, particularly those with gaming experience, identify and understand the roles of each component in the game and recognize the game's educational objectives.     

Playful public participation in urban planning: A case study for online serious games

The aim of this paper is to study the implementation of online games to encourage public participation in urban planning. Its theoretical foundations are based on previous work in public participatory geographical information systems (PP GISs), play and games, with a special focus on serious games. Serious games aim to support learning processes in a new, more playful way. We developed the concept of playful public participation in urban planning, including playful elements such as storytelling, walking and moving, sketching, drawing, and games. A group of students designed an online serious public participatory game entitled NextCampus. The case study used in NextCampus was taken from the real-world question of a possible move of a university campus to a new location in the city of Hamburg, Germany. The development of the serious public participatory game NextCampus resulted in a physical prototype, user interface design, and a computational model of the game. The NextCampus game was tested with the help of two groups of urban planning students and presented to three external experts who provided valuable recommendations for further development. The critical comments questioned the level of complexity involved in such games. The positive comments included recognition of the potential for joy and the playfulness a game like NextCampus could evoke.     

Teaching computer game design and construction

Computer gaming is a key component of the rapidly growing entertainment industry. While building computer games has typically been a commercial endeavor, we believe that designing and constructing a computer game is also a useful activity for educating students about geometric modeling and computer graphics. In particular, students are exposed to the practical issues surrounding topics such as geometric modeling, rendering, collision detection, character animation and graphical design. Moreover, building an advanced game provides students exposure to the real-world side of software engineering that they are typically shielded from in the standard computer class. In this paper, we describe our experiences with teaching a computer science class that focuses on designing and building the best game possible in the course of a semester. The paper breaks down a typical game into various components that are suited for individual student projects and discusses the use of modern graphical design tools such as Maya in building art for the game. We conclude with a rough timeline for developing a game during the course of a semester and review some of the lessons learned during the three years we have taught the class.     

Evolutionary collective behavior decomposition model for time series data mining

In this research, we propose a novel framework referred to as collective game behavior decomposition where complex collective behavior is assumed to be generated by aggregation of several groups of agents following different strategies and complexity emerges from collaboration and competition of individuals. The strategy of an agent is modeled by certain simple game theory models with limited information. Genetic algorithms are used to obtain the optimal collective behavior decomposition based on history data. The trained model can be used for collective behavior prediction. For modeling individual behavior, two simple games, the minority game and mixed game are investigated in experiments on the real-world stock prices and foreign-exchange rate. Experimental results are presented to show the effectiveness of the new proposed model.     

Evaluation of semi-automatically generated accessible interfaces for educational games

The increasing body of evidence supporting the use of videogames in educational settings (usually referred to as serious games) is pushing their deployment across different areas of the educational system. However, this increased adoption also raises serious ethical issues: videogames are one of the least accessible forms of multimedia, and if education is to embrace serious games, there is an imperative need for universal accessibility in serious games to prevent a digital divide. However, producing accessible games is expensive and effort consuming, and serious games development already fare with limited budgets. In this work we explore the potential impact of the (semi-) automatic adaptation of game interfaces as a way to facilitate accessible game development (and thus trim the cost down). We propose a game interface model optimized for point-and-click adventure games, a popular genre among serious games that we have used to perform different semi-automatic adaptations in a game. We have tested the resulting adapted game with end users with specific disability profiles. Our tests discovered that the automatic adaptations produced usable games that retained part of their attractive, although different usability issues had a negative impact on the user experience. We also discuss the origins of such limitations and propose possible remediation actions, as well as a refined interface model.     

Interactive story authoring: A viable form of creative expression for the classroom

The unprecedented growth in numbers of children playing computer games has stimulated discussion and research regarding what, if any, educational value these games have for teaching and learning. The research on this topic has primarily focused on children as players of computer games rather than builders/constructors of computer games. Recently, several game companies, such as BioWare Corp. and Bethesda Softworks, have released game story creation tools to the public, along with their games. However, a major obstacle to using these commercial tools is the level of programming experience required to create interactive game stories. In this paper, we demonstrate that a commercial game story construction tool, BioWare Corp.’s Aurora Toolset, can be augmented by our new tool, ScriptEase, to enable students in two grade ten English classes to successfully construct interactive game stories. We present evidence that describes the relationship between interactive story authoring and traditional story authoring, along with a series of factors that can potentially affect success at these activities: gender, creativity, intellectual ability, previous experiences with programming, time playing computer games, and time spent online. Results indicate that students can successfully construct sophisticated interactive stories with very little training. The results also show no gender differences in the quality of these interactive stories, regardless of programming experience or the amount of time per week playing computer games or participating in general online activities, although a subset of female students did show a slightly higher level of performance on interactive story authoring. In the educational context of this study, we show that ScriptEase provides an easy-to-use tool for interactive story authoring in a constructionist learning environment.     

Equilibria problems on games: Complexity versus succinctness

We study the computational complexity of problems involving equilibria in strategic games and in perfect information extensive games when the number of players is large. We consider, among others, the problems of deciding the existence of a pure Nash equilibrium in strategic games or deciding the existence of a pure Nash or a subgame perfect Nash equilibrium with a given payoff in finite perfect information extensive games. We address the fundamental question of how can we represent a game with a large number of players? We propose three ways of representing a game with different degrees of succinctness for the components of the game. For perfect information extensive games we show that when the number of moves of each player is large and the input game is represented succinctly these problems are PSPACE-complete. In contraposition, when the game is described explicitly by means of its associated tree all these problems are decidable in polynomial time. For strategic games we show that the complexity of deciding the existence of a pure Nash equilibrium depends on the succinctness of the game representation and then on the size of the action sets. In particular we show that it is NP-complete, when the number of players is large and the number of actions for each player is constant, and that the problem is -complete when the number of players is a constant and the size of the action sets is exponential in the size of the game representation. Again when the game is described explicitly the problem is decidable in polynomial time.     

Gamification: A framework for designing software in e-banking

The gamification software development gave emphasis to the role played by the users to test and improve the software. This study presents a framework for software gamified in e-banking, taking a users' groups and a qualitative research approach, to check the users' design preferences in five cases of banking software gamified (Futebank, Dreams, Galaxy, Olympics, and Warrants). After software presentation, and usage experience, 53 participants, responses to a survey with six open questions. The data were analyzed through a text semantic software, to detect and classify lexical items in, accordance, with standard of software quality characteristics and user experiences. Two primary categories were identified, as well five dimensions in each element and characteristic categories. The results show five characteristic dimensions (design, appearance, functionality, rules, and objectives) and five element dimension (game, product, security, process, and information). These findings provide a framework for web designers and e-business, highlighting the most important software features when dealing with serious applications with game design. It adds value to the current literature on understanding the customer relationship with the game and the financial product, identifying new dimensions (game and product) on the approach of thinking and design gamification in e-banking. Our finding contributes to a better understanding of key elements and characteristics in e-banking software design and has important practical implications for software development and marketing practices. Thoughts on the users' software design preferences identified, should propel increase adoption and attractiveness of online banking.     

New Algorithms for Solving Simple Stochastic Games

We present new algorithms for determining optimal strategies for two-player games with proba- bilistic moves and reachability winning conditions. Such games, known as simple stochastic games, were extensively studied by A.Condon [Anne Condon. The complexity of stochastic games. Information and Computation, 96(2):203–224, 1992, Anne Condon. On algorithms for simple stochastic games. In Jin-Yi Cai, editor, Advances in Computational Complexity Theory, volume 13 of DIMACS Series in Discrete Mathematics and Theoretical Computer Science, pages 51–73. AMS, 1993]. Many interesting problems, including parity games and hence also mu-calculus model checking, can be reduced to simple stochastic games. It is an open problem, whether simple stochastic games can be solved in polynomial time. Our algorithms determine the optimal expected payoffs in the game. We use geometric interpre- tation of the search space as a subset of the hyper-cube [0,1]^N. The main idea is to divide this set into convex subregions in which linear optimization methods can be used. We show how one can proceed from one subregion to the other so that, eventually, a region containing the optinal payoffs will be found. The total number of subregions is exponential in the size of the game but, in practice, the algorithms need to visit only few of them to find a solution. We believe that our new algorithms could provide new insights into the difficult problem of deter- mining algorithmic complexity of simple stochastic games and other, equivallent problems.     

Modeling Multileader–Follower Noncooperative Stackelberg Games

This paper presents a Stackelberg–Nash game for modeling multiple leaders and followers. The model involves two Nash games restricted by a Stackelberg game. We propose a computational approach to find the equilibrium point based on the extraproximal method for ergodic controlled finite Markov chains. The extraproximal method consists of a two-step iterated procedure: the first step is a prediction and the second is a basic adjustment of the previous step. We formulate the game as coupled nonlinear programming problems using the Lagrange principle. The Tikhonov’s regularization method is used to guarantee the convergence to a unique equilibrium point. Validity of the method is demonstrated applying this framework to model an oligopoly competition.     

Studying the effects of computer serious games on people with intellectual disabilities or autism spectrum disorder: A systematic literature review

This study examines the available literature on the effects of serious games on people with intellectual disabilities or autism spectrum disorder. The studies were categorized based on the limitations in skills that these people address. Fifty‐four studies were selected, from different data sources. These studies address limitations in intellectual functioning and adaptive behaviour. The results showed that the majority of studies on the effects of serious games for people with intellectual disabilities or autism spectrum disorder had a positive impact. Also, most studies for people with autism aim to improve social and communicational skills, whereas conceptual and cognitive skills were mainly observed in studies for people with intellectual disabilities. Although this study covers serious games in all platforms or delivery systems, the overwhelming majority of the presented studies include computer serious games. Computer‐assisted learning through serious games is considered quite promising for people with intellectual disabilities or autism spectrum disorder.     

Impacts of behavioral engagement and self-monitoring on the development of mental models through serious games: Inferences from in-game measures

The present study investigated the potential of serious games for the acquisition of complex cognitive skills by assessing learners’ mental model development, operationalized as an increase in Mental Model Accuracy (MMA). Furthermore, we assessed behavioral engagement and self-monitoring as two specific engagement types within the gameplay process and analyzed their impact on mental model development. German undergraduate students (N = 97) played a serious game developed to foster practical money skills. We obtained pre- and post-gaming measures of MMA to analyze the development of mental models by applying a structural assessment method. Unobtrusive measures of behavioral engagement and self-monitoring were obtained by computerized collection of participants’ in-game activities. Although we did not find a significant increase in overall MMA through playing, the degree of self-monitoring had a significant and positive effect on post-gaming MMA, even beyond the effect of initial MMA. Behavioral engagement had no impact on mental model development; however, it was positively related to self-monitoring behavior. The results are discussed in light of findings from research on self-regulated learning and controversial notions regarding the effect of behavioral engagement in serious games. In addition to insights into gameplay processes that affect mental model development through serious games, the present study also has practical implications in stressing the importance for game designers to provide learners with the opportunity to engage in self-monitoring behavior while playing a serious game.     

Algorithms for Finding Repeated Game Equilibria

This paper describes computational techniques for finding all equilibria in infinitely repeated games with discounting and perfect monitoring. It illustrates these techniques with a three player Cournot game. This is the first infinitely repeated three player game ever solved. The paper also presents the solution for the set of equilibria in a two country tariff war. In both games the set of equilibria is large even when the players are not patient.     

What makes good games go viral? The role of technology use,efficacy, emotion and enjoyment in players’ decision to share a prosocial digital game

Serious digital games may be an effective tool for prosocial message dissemination because they offer technology and experiences that encourage players to share them with others, and spread virally. But little is known about the factors that predict players’ willingness to share games with others in their social network. This panel study explores how several factors, including sharing technology use, emotional responses, and game enjoyment, contribute to players’ decision to share the game Darfur is Dying, with others. College students played the game and completed questionnaires that assessed whether they had shared the games at two different time points: during game play and after game play. Positive emotions predicted sharing while students played the game, but negative emotions predicted whether the game was shared after initial game play. Game enjoyment predicted players’ intentions to share the game, but it did not predict actual sharing behavior. Neither players’ general use of sharing technologies nor their satisfaction related to sharing digital content predicted sharing intentions or behavior. These findings have implications for the study of viral social marketing campaigns, and serious game design and theory.     

Serious Game for Children with Autism to Learn Vocabulary: An Experimental Evaluation

The use of serious games (SGs) to provide intervention for various skills to children with autism spectrum disorder (ASD) has increased in the recent years. However, the potential of these games has not been utilized to provide learning of vocabulary to children with ASD. In designing games for children with ASD, there is a need to consider components specifically from the perspectives of ASD and the generic components that can support from the theoretical, content, and game design aspects. In the absence of any existing framework to design games for children with ASD, this article first introduces a framework named serious game design framework (SGDF), constructed to provide support throughout the design process. This framework was constructed based on the extensive review of the literature on ASD and existing SGDFs. The article then focuses on the design and development of a SG prototype based on SGDF. An experimental evaluation prototype was conducted to examine the effectiveness using the withdrawal design of single-subject research design (SSRD) in improving the receptive identification of vocabulary items among children with autism before and after using the prototype. The receptive identification of vocabulary items is measured in terms of the number of correct responses given and the number of attempts made to identify the correct response. The pre- and post-evaluations of the SG prototype show that learning of vocabulary items among children with ASD improved after using the game and they retained items at the end of weeks 1 and 2 following the withdrawal of intervention.     

Adaptive difficulty scales for Parkour games

Mobile computer games have become increasingly popular in recent years. A major factor for successful game development is the adequate control of the game׳s difficulty. This paper discusses justification for dynamic difficulty adaption for Parkour games. It presents an adaptive mechanism for difficulty adjustment in response to the player׳s run-time performance in the single player mode. The mechanism is based on game content generation techniques, considering constrains for mobile screens. Both the functionality of the game׳s objects and the player׳s psychological and behavioral inclinations are taken into consideration. Our preliminary experiment shows that game experiences are significantly enhanced with the adaption mechanism.     

EXPERIMENTS WITH ONLINE REINFORCEMENT LEARNING IN REAL-TIME STRATEGY GAMES

Real-time strategy (RTS) games provide a challenging platform to implement online reinforcement learning (RL) techniques in a real application. Computer, as one game player, monitors opponents’ (human or other computers) strategies and then updates its own policy using RL methods. In this article, we first examine the suitability of applying the online RL in various computer games. Reinforcement learning application depends on both RL complexity and the game features. We then propose a multi-layer framework for implementing online RL in an RTS game. The framework significantly reduces RL computational complexity by decomposing the state space in a hierarchical manner. We implement an RTS game—Tank General—and perform a thorough test on the proposed framework. We consider three typical profiles of RTS game players and compare two basic RL techniques applied in the game. The results show the effectiveness of our proposed framework and shed light on relevant issues in using online RL in RTS games.     

A service composition oriented framework for configuring SMeet multiparty collaboration environments

To enable remote collaboration among knowledge workers, there has been extensive research about prototyping network-based multiparty collaboration environments. Particularly, it is necessary to solve the configuration difficulties that arise from different settings of various tools in traditional room-based collaboration systems. To ease these difficulties, in this paper, we design a service composition oriented framework for the SMeet (Smart Meeting Space) multiparty collaboration environments by following the SOA (service oriented architecture) design principles. The proposed framework aims to facilitate the flexible configuration of diverse networked devices and associated application tools for successful multiparty collaboration. According to a pre-defined template, it helps the operators and users to compose services that are dispersed across remote sites. By leveraging open-source agent middleware, we also develop a SMeet toolkit with GUIs (graphical user interfaces) to assist the easily-configurable realization of SMeet multiparty collaboration environments. The developed SMeet toolkit is utilized to realize a remote collaboration scenario between two SMeet prototype sites, by enabling the network-based interactive sharing of HD-quality media on networked tiled displays (NeTDs).