Computer Game

Pathfinding represents a fundamental challenge in computer science with applications ranging from robotics to video game development. This paper presents a comprehensive comparative analysis of three prominent pathfinding algorithms: A* Search, Dijkstra's Algorithm, and Greedy Best-First Search. The research examines these algorithms' performance characteristics through empirical testing on standardized grid-based environments, measuring efficiency in terms of path optimality, computational time, and memory usage. Our findings demonstrate that while A* Search consistently produces optimal paths with reasonable efficiency, the choice of algorithm depends heavily on specific application requirements including available computational resources and optimality constraints. The study provides practical guidelines for algorithm selection in real-world pathfinding scenarios and identifies potential hybrid approaches for future research.

This descriptive study explores the multifaceted impact of gaming on children's cognitive development and behavioral modification. With the increasing prevalence of digital gaming in children's lives, understanding its effects is crucial. This paper reviews existing literature, examining both positive and negative cognitive effects like attention, memory, problemsolving, and spatial reasoning, alongside behavioral changes such as aggression, social interaction, and impulsivity. The study aims to provide a comprehensive overview of the current understanding of gaming's influence on children, highlighting areas warranting further research and offering insights for parents, educators, and policymakers.

A leaf polygon decimation method, Progressive Leaves Union (PLU), is presented to gradually diminish the number of sparse polygons while approximately keeping the spatial occupation and color distribution of the foliage. In each step of decimation, a new leaf is constructed to represent other two leaves close in position and similar in shape. Many measurements of similarity are used to choose the best leaf pair to be united. All steps of simplification are recorded in preprocessing, and appropriate simplified models are chosen for different viewing positions and for different resolutions in visualization. Experiments have shown that PLU keeps visual effect of original foliage, and when combined with branch polygon simplification, is efficient for multi-resolution representation and view-dependent plant community visualization.

PurposeThis paper seeks to present findings from an SME case study situated in the computer games industry, the youngest and fastest growing of the new digital industries. The study aims to examine changing people management practices as the case company undergoes industry‐typical strategic change to embark on explorative innovation and it seeks to argue that maintaining an organisational context conducive to innovation over time risks turning into a contest between management and employees, as both parties interpret organisational pressures from their different perspectives.Design/methodology/approachA single case study design is used as the appropriate methodology to generate in‐depth qualitative data from multiple organisational member perspectives.FindingsFindings indicate that management and worker perspectives on innovation as strategic change and the central people management practices required to support this differ significantly, resulting in tensions and organisational str...

The Boolean Decision tree model is perhaps the simplest model that computes Boolean functions; it charges only for reading an input variable. WE study the power of randomness (vs. both determinism and non-determinism) in this model, and prove separation results between the three complexity measures. These results are obtained via general and efficient methods for computing upper and lower bounds on the probabilistic complexity of evaluating Boolean formulae in which every variable appears exactly once (AND/OR tree with distinct leaves). These bounds are shown to be exactly tight for interesting families of such tree functions. We then apply our results to the complexity of evaluating game trees, which is a central problem in $AI$. These trees are similar to Boolean tree functions, except that input variables (leaves) may take values from a large set (of valuations to game positions) and the AND/OR nodes are replaced by MIN/MAX nodes. Here the cost is the number of positions (leaves) probed by the algorithm. The best-known algorithm for this problem is the alpha-beta pruning method. As a deterministic algorithm, it will in the worst case have to examine all positions. Many papers studied the expected behavior of alpha-beta pruning (or uniform trees) under the unreasonable assumption that position values are drawn independently from some distribution. We analyze a randomized variant of alpha-beta pruning, show that it is a considerably faster than deterministic one in worst case, and prove it optimal for uniform trees.

This paper describes the use of a new swarm-based metaheuristic, namely Krill Herd Algorithm (KHA), in computer gaming. In this work, KHA is employed to find a bots movement strategy in a computer racing game. The complete algorithm is implemented using a Unity Engine in C# language. Herein, the triggering of the metaheuristic optimization task was conducted by the way of a KHA internal parameter investigation. In this approach, the goal of the race (the KHA evaluation function) for both the human and computer player is to finish a lap in the shortest time possible.

Abstract: HIV/AIDS continues to be a menace to the global community, especially in sub-Saharan Africa and South Africa is not an exception. The infection rate is continues to grow, in particular, among the young adults. Cell phones have been identified as one of the tools that can be used to overcome the challenge of information dissemination regarding HIV/AIDS among young adults because of its acceptability within this age group. Access to appropriate information can be a powerful for prevention and management of many chronic illnesses, including hypertension, diabetes and HIV/AIDS. Within the young adults age group information access by use of Short Messaging Services (SMS) becomes particularly appealing. In this regard, it is proposed to provide access to carefully screened information on HIV/AIDS within the context of frequently asked questions (FAQ) system. However, automating SMS-based information search and retrieval poses significant challenges because of the inherent noise ...

Mobile phones are ubiquitous with millions of users acquiring them every day for personal, business and social usage or communication. Its enormous pervasiveness has created a great advantage for its use as a technological tool applicable to overcome the challenges of information dissemination regarding burning issues, advertisement, and health related matters. Short message services (SMS), an integral functional part of cell phones, can be turned into a major tool for accessing databases of information on HIV/AIDS as appreciable percentage of the youth embrace the technology. The common features by the users of the unique language are the un-grammatical structure, convenience of spelling, homophony of words and alphanumeric mix up of the arrangement of words. This proves it to be difficult to serve as query in the search engine architecture. In this work SMS query was used for information accessing in Frequently Asked Question FAQ system under a specified medical domain. Finally, when the developed system was measured in terms of proximity to the answer retrieved remarkable results were observed..

Language usage over the computer-mediated discourses differ significantly from the language of communication from person-to-person or tribe-to-tribe, the same applies to information retrieval mechanism. Few years ago, the primary technologies used to construct large information systems were database systems, information retrieval systems, and information filtering approaches. Database systems were used to handle large volumes of structured data and to provide guarantees of reliability and consistency despite systems failures and high volumes of update transactions. Information retrieval systems were used to search large databases of text, such as encyclopedia materials with hundreds of thousands of articles, biographies, videos, abstracts, legal materials, or newspaper stories. Information filtering approaches provide periodic updates in the form of text stories, mostly in the business domain, based on user profiles and it is always specific. Relatively for this short period, there have been Manuscript

Developing computer game agents is often a lengthy and expensive undertaking. Detailed domain knowledge and decision-making procedures must be encoded into the agent to achieve realistic behavior. In this paper, we simplify this process by using the ICARUS cognitive architecture to construct game agents. The system acquires structured, high fidelity methods for agents that utilize a vocabulary of concepts familiar to game experts. We demonstrate our approach by first acquiring behaviors for football agents from video footage of college football games, and then applying the agents in a football simulator.

Developing autonomous agents for computer games is often a lengthy and expensive undertaking that requires manual encoding of detailed and complex knowledge. In this paper we show how to acquire hierarchical skills for controlling a team of simulated football players by observing video of college football play. We then demonstrate the results in the Rush 2008 football simulator, showing that the learned skills have high fidelity with respect to the observed video and are robust to changes in the environment. Finally, we conclude with discussions of this work and of possible improvements.

Transfer of learned knowledge from one task to another offers an opportunity to reduce development cost of knowledgebased systems by reusing existing knowledge in novel situations. However, minor differences in the initial and target environments can reduce the effectiveness of the system substantially. In previous work, we presented a system that acquired procedural knowledge of American football from video footage, and then applied it to controlling players in a simulated environment. In this paper, we extend that system by adding the ability to adapt the transferred procedures to better fit the simulator. We show that even when the transferred structural knowledge provides a quality starting point for performance in the game environment, a simple parameter optimization technique can significantly improve its performance and utility.

This review article explores the current landscape of computer vision applications in American football, with the goal of informing the development of a comprehensive, automated play analysis software. It examines existing research, including nine key papers and expert insights from a detailed video transcript, to provide a thorough analysis of current methodologies and future directions. The proposed software aims to analyze football footage from various sources, providing detailed breakdowns of offensive and defensive plays, player tracking, and statistical analysis through an accessible interface. This would democratize advanced analytical tools, currently limited to elite levels of the sport, for a broader audience of players, coaches, and fans. The article synthesizes findings on player and jersey number recognition, field reconstruction, and event detection, highlighting how these individual components can be integrated into a single, streamlined solution. It also addresses the challenges of data collection and model training, proposing data augmentation and advanced neural network architectures as viable solutions. Ultimately, this review serves as a foundational document, outlining the path forward for creating a tool that could revolutionize football film study and strategic planning at all levels of the game.

The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness detection primarily make pre-assumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here we employ machine learning to datamine actual human behavior during drowsiness episodes. Automatic classifiers for 30 facial actions from the Facial Action Coding system were developed using machine learning on a separate database of spontaneous expressions. These facial actions include blinking and yawn motions, as well as a number of other facial movements. In addition, head motion was collected through automatic eye tracking and an accelerometer. These measures were passed to learning-based classifiers such as Adaboost and multinomial ridge regression. The system was able to predict sleep and crash episodes during a driving computer game with 96% accuracy within subjects and above 90% accuracy across subjects. This is the highest prediction rate reported to date for detecting real drowsiness. Moreover, the analysis revealed new information about human behavior during drowsy driving.

The advance of computing technology has provided the means for building intelligent vehicle systems. Drowsy driver detection system is one of the potential applications of intelligent vehicle systems. Previous approaches to drowsiness detection primarily make pre-assumptions about the relevant behavior, focusing on blink rate, eye closure, and yawning. Here we employ machine learning to datamine actual human behavior during drowsiness episodes. Automatic classifiers for 30 facial actions from the Facial Action Coding system were developed using machine learning on a separate database of spontaneous expressions. These facial actions include blinking and yawn motions, as well as a number of other facial movements. In addition, head motion was collected through automatic eye tracking and an accelerometer. These measures were passed to learningbased classifiers such as Adaboost and multinomial ridge regression. The system was able to predict sleep and crash episodes during a driving computer game with 96% accuracy within subjects and above 90% accuracy across subjects. This is the highest prediction rate reported to date for detecting real drowsiness. Moreover, the analysis revealed new information about human behavior during drowsy driving.

Online computer games show potential not just for engaging and entertaining users, but also in promoting learning. Especially in Turkey children spend long hours playing computer games, which are mostly in English, in internet cafés. This qualitative research based on phenomenological theoretical framework investigates young learners' experiences of language learning while playing computer games in internet cafes. The data was collected through observations and semi-structured interviews and analyzed through phenomenological data analysis steps. Implications put light into integrating computer games to ELT curriculum.

The research team applies narrative theory to design a location based context-aware mobile role playing game in order to make students feel that they are living in the game world and role playing an actor, exploring the game world, completing the quests, and learning things. The research finds that students' confidence of playing computer games and degree of liking computer games do not influence their voluntariness of using such game in the future; on the contrary, their attitude towards computer games and how they feel comfortable to computer games significantly influence their voluntariness of using such game.

The predictability of culture, gender, and media use for dream type information in Canadian students was the focus of this inquiry. Independent variables were gender (sex of subject and relative masculinity and femininity) culture; (ethnic identity and self-construal of independence versus interdependence) and media use (various gaming, social media , and cell phone questions). These were regressed onto several dream content related dependent variables. These were gathered using the Dream Intensity Scale and research participant and judges evaluations of a recent dream. Gender variables were better able to predict content of self-report dream measures while gender variables showed no difference from media use or culture in predicting judge's evaluations of dream content.

Canadian students of varying cultural backgrounds took an online survey for course credit examining their dream experiences (Dream Intensity Scale, DIS; Yu, 2010) and history of media use, i.e., social media and video game play. Regression analyses onto the data found that the role of sex and culture, relative to history of media use, was strongest with total DIS scores as well as dream recall and nightmare information, which is often reported in the literature. Media use was also a component of these two dimensions but its role in predicting self-reported dream experiences was stronger for the other types of DIS information. In general the findings with media use seem to fall around age the subject began using social media or gaming as well as their use of MySpace, one of the first social media sites and thus presumably longest used. These findings support Lambrecht, Schredl, Henley-Einion, and Blagrove (2013) in terms of the continuity hypothesis of dreaming and high frequency of ...

A new waking influence has emerged that is becoming so widely experienced that it bears further consideration in its own right as to it's influence on subsequent night time dreams. That is, digital life. It ranges from listening to music to texting to checking facebook status to playing video games to information checking. All of these activities are computer mediated. In this inquiry, students at a western Canadian university indicated if they had played computer games or used the computer for non-gaming purposes during the day prior to a recent dream they reported. Respondents indicated their confidence about the type of dream they reported as well their video game play habits and generic media used the day prior to the dream. There was some indication that the high end non-gaming computer use group had more lucid (females only) and control dreams but less bizarre dreams. Unlike previous research there were no differences in nightmares or bad dreams among groups. This was discussed in terms of previous video game play and dreams research.

Many day-to-day applications involve autonomous agents. When designing autonomous agents, the problem of selecting actions must be considered, as it governs decision making at all times. In this paper we describe how we designed intelligent virtual cognitive agents representing operators performing tasks in a high-risk plant. They must respond to expected as well as unexpected events. The reasoning system controlling the agent behavior is designed to exhibit human behavior. Agents must be able to plan their actions according to their perception, their beliefs and their goals. We developed a planning system that interleaves plan construction and plan execution. The new planner, called AATP 1 , produces a plan according to agent goal.

O estudo realizado 4 , apoiado em pesquisas sobre cultura moral na perspectiva teórica piagetiana, teve como objetivo investigar a relação entre virtude e regra nos procedimentos de participantes do jogo virtual Colheita Feliz, do aplicativo do Orkut. A pesquisa qualitativa, na modalidade de um estudo descritivo, analisou as condutas lúdicas de 60 jogadores, os quais foram observados durante dois meses. O ranking revelador do desempenho dos jogadores foi analisado em correspondência às observações dos procedimentos empregados. Os resultados apontam o predomínio do procedimento de roubo em relação ao de cultivo de produtos e permitem considerar que a ação de roubar, dominante nas suas condutas, não foi regida pela virtudehonestidade ou ausência dela (domínio moral) -, mas pela convenção das regras do jogo (domínio social), que favorecem tal procedimento, combinadas com o domínio pessoal (escolhas) e o mútuo consentimento entre os sujeitos participantes do jogo. Os dados não indicam relação entre as ações dos jogadores no campo virtual e no plano real, no que concerne ao roubo, e reforçam a ideia de que a regra é convencionada nos domínios de um grupo e é dependente das interações sociais nele estabelecidas, nas quais deve prevalecer o respeito mútuo entre pares. Os dados revelam, ainda, que a moral não é o elemento regulador das ações no jogo. Infere-se a importância do estudo de procedimentos de jogadores em jogos virtuais como reveladores de aspectos cognitivos, afetivo-sociais e morais aplicados em situações de interação lúdica.

It is well known that a computer game other than video games is a current trend among the younger generation. Studies have shown that the use of computer games not only played by children as young as two years even up to adulthood. Integration and implementation of computer games into the classroom is also seen to help students learn with more fun and effective. The purpose of this paper is to discuss the principles of learning to be embedded in a computer game-based learning as well as aspects that can be considered when designing a computer game that will be used as the application of teaching and student learning.

Inspection-based evaluation methods predicting usability problems can be applied for evaluating products without involving users. A new method (named SEEM), inspired by Norman's theory-of-action model [18] and Malone's concepts of fun , is described for predicting usability and fun problems in children's computer games. This paper describes a study to assess SEEM's quality. The results show that the experts in the study predicted about 76% of the problems found in a user test. The validity of SEEM is quite promising. Furthermore, the participating experts were able to apply the inspection-questions in an appropriate manner. Based on this first study ideas for improving the method are presented.

This paper describes a study which examines whether a predictive evaluation method (SEEM) is suitable to assess products for an older age group than for which the evaluation method was originally developed. SEEM stands for Structured Expert Evaluation Method and is an analytical evaluation method especially developed for assessing the fun and usability of young children's educational computer games (children from 5 to 7 years old). In the present study SEEM was applied to assess educational computer games for children between 9 and 11 years old. Outcomes on scores for thoroughness (whether SEEM finds all problems), validity (whether SEEM makes predictions that are likely to be true) and appropriateness (whether SEEM is applied correctly) were compared. The results show that the trends for the thoroughness and the validity are the same for the two different age groups; however SEEM scores a bit better for the oldest age group. The appropriateness scores are about the same for the two age groups. The results indicate that SEEM can also be applied for assessing educational computer games for children between 9 and 11 years old.

In this paper the development and assessment of a new formative evaluation method called the problem identification picture cards (PIPC) method is described. This method enables young children to express both usability and fun problems while playing a computer game. The method combines the traditional thinking-aloud method with picture cards that children can place in a box to indicate that there is a certain type of problem. An experiment to assess this method shows that children may express more problems (verbally, or with a picture card, or with a combination of a picture card and a verbalisation) with the PIPC method than without this method (in which they can only indicate problems verbally). Children in the experiment did not just replace verbalisations by using the provided picture cards and some children preferred to use the PIPC method during the test instead of the standard thinking-aloud method. The PIPC method or some aspects of the method could be a good instrument to increase the amount of information expressed by young children during an evaluation.

The current research study replicated a study by Rogers et al. (Rogers M, Smoak ND, Liu J. Self-reported criminal computer behavior: a big-5, moral choice and manipulative exploitive behavior analysis. Deviant Behavior 2006;27:1-24) and examined the psychological characteristics, moral choice, and exploitive manipulative behaviors of self-reported computer criminals and non-computer criminals. Seventy-seven students enrolled in an information technology program participated in the web-based study. The results of the study indicated that the only significant variable for predicting criminal/deviant computer behavior was extraversion. Those individuals self-reporting criminal computer behavior were significantly more introverted than those reporting no criminal/deviant computer behavior. This finding is contrary to the findings of the previous study. The current study confirmed that the four psychometric instruments were reliable for conducting research in the field of criminal/deviant computer behavior. The impact of the findings on the field of digital forensic investigations is discussed as well as possible reasons for the apparent contradiction between the two studies.

This quasi-experimental study with pre test-post test and control group investigated a comparison about the impact of the SCAFFOLDING TEACHING METHOD and the TRADITIONAL TEACHING METHOD on ACADEMIC MOTIVATION of high school second grade students in English lesson in Veisian in Lorestan province. The study population was high school second grade male students of Veisian in 2010-2011. The sample size was 40 students, in which 20 were in the experimental group and 20 were in control group who were selected by multistage cluster sampling. In the experimental group the scaffolding teaching and in control group TRADITIONAL TEACHING METHOD s were used. The research tool was Verland ACADEMIC MOTIVATION Inventory (1985). For data analysis; both descriptive and inferential statistics (ANOVA) were used. The results showed a significant differences among the ACADEMIC MOTIVATION of the two groups (P< 0.05) and experimental group was affected more by SCAFFOLDING TEACHING METHOD in comparison with control group (P< 0.05). So teachers need to use the SCAFFOLDING TEACHING METHOD in class to increase the student’s ACADEMIC MOTIVATION.

Intrusive memories (IMs) after traumatic events can be distressing and disrupt mental health and functioning. We evaluated the impact of a brief remotely-delivered digital imagery-competing task intervention on the number of IMs for intensive care unit (ICU) staff who faced repeated trauma exposure during the COVID-19 pandemic using a two-arm, parallel-group, single-blind randomised controlled trial, with the comparator arm receiving delayed access to active treatment (crossover). Eligible participants worked clinically in a UK NHS ICU during the pandemic and had at least 3 IMs of work-related traumatic events in the week before recruitment. Participants were randomly assigned (1:1) to immediate (weeks 1-4) or delayed (weeks 5-8) intervention access. Sequential Bayesian analyses to optimise the intervention and increase trial efficiency are reported elsewhere . The primary endpoint for the pre-specified frequentist analysis of the final study population compared the number of IMs experienced in week 4 between the immediate and delayed access arms. Secondary outcomes included clinical symptoms, work functioning and wellbeing. Safety was assessed throughout the trial by scheduled questions and free report. All analyses were undertaken on an intention-to-treat basis (86 randomised participants). There were significantly fewer intrusive memories during week 4 in the immediate (median = 1, IQR = 0-3, n = 43), compared to the comparator delayed arm (median = 10, IQR = 6-17, n = 43), IRR 0.31, 95% CI: 0.20-0.48, p < 0.001. After crossover, the delayed arm also showed a significant reduction in IMs at week 8 compared to week 4. There were convergent findings for symptoms of PTSD, insomnia and anxiety, work engagement and burnout, general functioning and quality of life. The intervention was found safe and acceptable to participants. All adverse events were unrelated to the study. Our study provides the first evidence of a benefit on reducing IMs, improving other clinical symptoms, work functioning and wellbeing, as well as safety of a brief remotely-delivered digital imagery-competing task intervention. An efficacy trial with an active control and longer follow-up is warranted. The trial is registered at ClinicalTrials.gov (NCT04992390).

Surgical simulators and computer games share the enabling technologies in the human-machine interface. With appropriate design and development, the computer-game-like medical training simulator could be used in surgical training. The authors describe a PC-based system for the simulation of the vertebroplasty procedure. In vertebroplasty, the surgeon or radiologist relies on sight and feel to properly insert the bone needle through various tissue types and densities and monitor the injection and reflux of the polymethylmethacrylate (PMMA), or cement, into the vertebra. This article focuses on the provision of a near-realistic haptic feel in bone needle insertion and manual PMMA injection. This involves an efficient biomechanical modeling of bone needle insertion and PMMA flow in bone for haptic rendering, as well as reliable delivery of forces via haptic devices. The authors show that with virtual reality gaming technologies, the surgical simulator can become a virtual trainer for a ...

To facilitate the development of spoken dialog systems and speech enabled applications, we introduce SGStudio (Semantic Grammar Studio), a grammar authoring tool that enables regular software developers with little speech/linguistic background to rapidly create quality semantic grammars for automatic speech recognition (ASR) and spoken language understanding (SLU). We focus on the underlying technology of SGStudio, including knowledge assisted example-based grammar learning, grammar controls and configurable grammar structures. While the focus of SGStudio is to increase productivity, experimental results show that it also improves the quality of the grammars being developed.

Designing agents whose behavior challenges human players adequately is a key issue in computer games development. This work presents a novel technique, based on reinforcement learning (RL), to automatically control the game level, adapting it to the human player skills in order to guarantee a good game balance. RL has commonly been used in competitive environments, in which the agent must perform as well as possible to beat its opponent. The innovative use of RL proposed here makes use of a challenge function, which estimates the current player's level, as well as changes on the action selection mechanism of the RL framework. The technique is applied to a fighting game, Knock'em, to provide empirical validation of the approach.

Industry pressures, including large full field simulation, modeling enhanced recovery from mature assets, and the rapid development of unconventional assets, are creating a huge demand for large, fast, high-fidelity reservoir simulation. Similar needs in seismic imaging have been addressed by running on GPUs, but the application of GPUs to something as complex as reservoir simulation presents challenges. We report on a practical multi-GPU approach to reservoir simulation that provides fast turn-around times on large models of upwards of tens of millions of cells on a single workstation. All major steps of the fully implicit CPR-AMG preconditioned black-oil simulation including property evaluation and Jacobian construction are directly evaluated on the GPUs. In this process, the abundant fine grain parallelism of the GPU cores are fully exposed and utilized. Because the simulations are memory-bandwidth bound, our data structures and algorithms are optimized to efficiently utilize the...

The structure of complex biological and socio-economic networks affects the selective pressures or behavioural incentives of components in that network, and reflexively, the evolution/behaviour of individuals in those networks changes the structure of such networks over time. Such &#x27;adaptive networks&#x27; underlie how gene-regulation networks evolve, how ecological networks self-organise, and how networks of strategic agents co-create social organisations. Although such domains are different in the details, they can each be ...

How can a system become better adapted over time without natural selection? Although some argue for &#x27;organismic&#x27;properties such as robustness and self-sustaining regulation in non-evolved systems [1, 5, 11], others insist that natural selection is the only source of true adaptation [3]. We suggest that understanding how adaptation can occur without natural selection remains a fundamental open question for the Artificial Life community. For example, the origin of life, the origin of evolution, and the origin of new units of selection in ...

When a dynamical system with multiple point attractors is released from an arbitrary initial condition it will relax into a configuration that locally resolves the constraints or opposing forces between interdependent state variables. However, when there are many conflicting interdependencies between variables, finding a configuration that globally optimises these constraints by this method is unlikely, or may take many attempts. Here we show that a simple distributed mechanism can incrementally alter a dynamical system such that it finds lower energy configurations, more reliably and more quickly. Specifically, when Hebbian learning is applied to the connections of a simple dynamical system undergoing repeated relaxation, the system will develop an associative memory that amplifies a subset of its own attractor states. This modifies the dynamics of the system such that its ability to find configurations that minimise total system energy, and globally resolve conflicts between inter...

This paper describes initiatives at Marist College to develop a Game Concentration in the undergraduate Computer Science curriculum. These initiatives contemplate recommendations for existing courses as well as adoption of new courses. We also consider activities of the Association of Computing Machinery (ACM) in this area and opportunities for students beyond the classroom.

The A-buffer (anti-aliased, area-averaged, accumulation buffer) is a general hidden surface mechanism suited to medium scale virtual memory computers. It resolves visibility among an arbitrary collection of opaque, transparent, and intersecting objects. Using an easy to compute Fourier window (box filter), it increases the effective image resolution many times over the Z-buffer, with a moderate increase in cost. The A-buffer is incorporated into the REYES 3-D rendering system at Lucasfilm and was used successfully in the “Genesis Demo” sequence in Star Trek II.

The usage of computer games by people with special needs sometimes can be difficult because some of them are not used to interact with a keyboard, mouse or gamepads. Some computer games even offer different paradigms of interaction but are no specifically designed to help people with special needs. We are currently facing the problem of developing a game to help Down syndrome children to interact with computers by the means of imitation. Our work presents the first step to provide an interaction framework to automatically recognize broad movements using computer vision concepts for movement recognition.

This paper presents an interactive genetic algorithm for generating a human-like autonomous player (bot) for the game Unreal Tournament 2004. It is based on a bot modelled from the knowledge of an expert human player. The algorithm provides two types of interaction: by an expert in the game and by an expert in the algorithm. Each one affects different aspects of the evolution, directing it towards better results regarding the agent's humanness (objective of this work). It has been conducted an analysis of the experts' influence on the performance, showing much better results after these interactions that the non-interactive version. The best bot were submitted to the BotPrize 2014 competition (which seeks for the best human-like bot), getting the second position.

In recent years, several Grand Challenges (GCs) of computing have been identified and expounded upon by various professional organizations in the U.S. and England. These GCs are typically very difficult problems that will take many hundreds, or perhaps thousands, of man-years to solve. Researchers involved in identifying these problems are not going to solve them. That task will fall to our students, and our students' students. Unfortunately for GC6, the Grand Challenge focusing on Dependable Systems Evolution, interest in formal methods-both by students and within computer science faculties-falls every year and any mention of mathematics in the classroom seems to frighten students away. So the question is: How do we attract new students in computing to the area of dependable software systems? Over the past several years at three universities we have experimented with the use of computer games as a target domain for software engineering project courses that focus on reliable systems engineering. This position paper summarizes our experiences in incorporating rigorous software engineering into courses with computer game projects.

This study evaluates and compares the suitability for child–computer interaction (CCI, the branch within human–computer interaction focused on interactive computer systems for children) of two devices: a standard computer mouse and the ENLAZA interface, a head mouse that measures the user’s head posture using an inertial sensor. A multidirectional pointing task was used to assess the motor performance and the users’ ability to learn such a task. The evaluation was based on the interpretation of the metrics derived from Fitts’ law. Ten children aged between 6 and 8 participated in this study. Participants performed a series of pre- and post-training tests for both input devices. After the experiments, data were analyzed and statistically compared. The results show that Fitts’ law can be used to detect changes in the learning process and assess the level of psychomotor development (by comparing the performance of adults and children). In addition, meaningful differences between the fi...

Developing computer game agents is often a lengthy and expensive undertaking. Detailed domain knowledge and decision-making procedures must be encoded into the agent to achieve realistic behavior. In this paper, we simplify this process by using the ICARUS cognitive architecture to construct game agents. The system acquires structured, high fidelity methods for agents that utilize a vocabulary of concepts familiar to game experts. We demonstrate our approach by first acquiring behaviors for football agents from video footage of college football games, and then applying the agents in a football simulator.

Two studies were conducted in order to determine the impact computer games had on the cognitive performance. Study 1 evaluated a measure of cognition, which incorporates aspects of short-term working memory, visual attention, mathematical decision making, and auditory perception. Study 2 measured the cognitive performance between those who did not play video games versus those who played either a violent or non-violent video game. Results from Study 1 indicate participants needed approximately four trials to reach asymptotic performance on the cognitive measure. Results of Study 2 showed that participants who did not play any video game did not have a change in their cognitive performance, while those who played either a violent or non-violent video game had an increase in their cognitive performance.