3,016 research outputs found
Proceedings of the SAB'06 Workshop on Adaptive Approaches for Optimizing Player Satisfaction in Computer and Physical Games
These proceedings contain the papers presented at the Workshop on Adaptive approaches
for Optimizing Player Satisfaction in Computer and Physical Games held at the Ninth
international conference on the Simulation of Adaptive Behavior (SAB’06): From
Animals to Animats 9 in Rome, Italy on 1 October 2006.
We were motivated by the current state-of-the-art in intelligent game design using
adaptive approaches. Artificial Intelligence (AI) techniques are mainly focused on
generating human-like and intelligent character behaviors. Meanwhile there is generally
little further analysis of whether these behaviors contribute to the satisfaction of the
player. The implicit hypothesis motivating this research is that intelligent opponent
behaviors enable the player to gain more satisfaction from the game. This hypothesis may
well be true; however, since no notion of entertainment or enjoyment is explicitly
defined, there is therefore little evidence that a specific character behavior generates
enjoyable games.
Our objective for holding this workshop was to encourage the study, development,
integration, and evaluation of adaptive methodologies based on richer forms of humanmachine
interaction for augmenting gameplay experiences for the player. We wanted to
encourage a dialogue among researchers in AI, human-computer interaction and
psychology disciplines who investigate dissimilar methodologies for improving gameplay
experiences. We expected that this workshop would yield an understanding of state-ofthe-
art approaches for capturing and augmenting player satisfaction in interactive systems
such as computer games.
Our invited speaker was Hakon Steinø, Technical Producer of IO-Interactive, who
discussed applied AI research at IO-Interactive, portrayed the future trends of AI in
computer game industry and debated the use of academic-oriented methodologies for
augmenting player satisfaction. The sessions of presentations and discussions where
classified into three themes: Adaptive Learning, Examples of Adaptive Games and Player
Modeling.
The Workshop Committee did a great job in providing suggestions and informative
reviews for the submissions; thank you! This workshop was in part supported by the
Danish National Research Council (project no: 274-05-0511). Finally, thanks to all the
participants; we hope you found this to be useful!peer-reviewe
Controlling Randomness: Using Procedural Generation to Influence Player Uncertainty in Video Games
As video games increase in complexity and length, the use of automatic, or procedural, content generation has become a popular way to reduce the stress on game designers. However, the usage of procedural generation has certain consequences; in many instances, what the computer generates is uncertain to the designer. The intent of this thesis is to demonstrate how procedural generation can be used to intentionally affect the embedded randomness of a game system, enabling game designers to influence the level of uncertainty a player experiences in a nuanced way. This control affords game designers direct control over complex problems like dynamic difficulty adjustment, pacing, or accessibility. Game design will be examined from the perspective of uncertainty and how procedural generation can be used to intentionally add or reduce uncertainty. Various procedural generation techniques will be discussed alongside the types of uncertainty, using case studies to demonstrate the principles in action
An Ecosystem Framework for the Meta in Esport Games
This paper examines the evolving landscape of modern digital games, emphasizing their nature as live services that continually evolve and adapt. In addition to engaging with the core gameplay, players and other stakeholders actively participate in various game-related experiences, such as tournaments and streaming. This interplay forms a vibrant and intricate ecosystem, facilitating the construction and dissemination of knowledge about the game. Such knowledge flow, accompanied by resulting behavioral changes, gives rise to the concept of a video game meta. Within the competitive gaming context, the meta represents the strategic and tactical knowledge that goes beyond the fundamental mechanics of the game, enabling players to gain a competitive advantage. We present a review of the state-of-the-art of knowledge for game metas and propose a novel model for the meta knowledge structure and propagation that accounts for this ecosystem, based on a review of the academic literature and practical examples. By exploring the dynamics of knowledge exchange and its influence on gameplay, the review presented here sheds light on the intricate relationship between game evolution, player engagement, and the associated emergence of game meta
How a Diverse Research Ecosystem Has Generated New Rehabilitation Technologies: Review of NIDILRR’s Rehabilitation Engineering Research Centers
Over 50 million United States citizens (1 in 6 people in the US) have a developmental, acquired, or degenerative disability. The average US citizen can expect to live 20% of his or her life with a disability. Rehabilitation technologies play a major role in improving the quality of life for people with a disability, yet widespread and highly challenging needs remain. Within the US, a major effort aimed at the creation and evaluation of rehabilitation technology has been the Rehabilitation Engineering Research Centers (RERCs) sponsored by the National Institute on Disability, Independent Living, and Rehabilitation Research. As envisioned at their conception by a panel of the National Academy of Science in 1970, these centers were intended to take a “total approach to rehabilitation”, combining medicine, engineering, and related science, to improve the quality of life of individuals with a disability. Here, we review the scope, achievements, and ongoing projects of an unbiased sample of 19 currently active or recently terminated RERCs. Specifically, for each center, we briefly explain the needs it targets, summarize key historical advances, identify emerging innovations, and consider future directions. Our assessment from this review is that the RERC program indeed involves a multidisciplinary approach, with 36 professional fields involved, although 70% of research and development staff are in engineering fields, 23% in clinical fields, and only 7% in basic science fields; significantly, 11% of the professional staff have a disability related to their research. We observe that the RERC program has substantially diversified the scope of its work since the 1970’s, addressing more types of disabilities using more technologies, and, in particular, often now focusing on information technologies. RERC work also now often views users as integrated into an interdependent society through technologies that both people with and without disabilities co-use (such as the internet, wireless communication, and architecture). In addition, RERC research has evolved to view users as able at improving outcomes through learning, exercise, and plasticity (rather than being static), which can be optimally timed. We provide examples of rehabilitation technology innovation produced by the RERCs that illustrate this increasingly diversifying scope and evolving perspective. We conclude by discussing growth opportunities and possible future directions of the RERC program
A Review on Energy Consumption Optimization Techniques in IoT Based Smart Building Environments
In recent years, due to the unnecessary wastage of electrical energy in
residential buildings, the requirement of energy optimization and user comfort
has gained vital importance. In the literature, various techniques have been
proposed addressing the energy optimization problem. The goal of each technique
was to maintain a balance between user comfort and energy requirements such
that the user can achieve the desired comfort level with the minimum amount of
energy consumption. Researchers have addressed the issue with the help of
different optimization algorithms and variations in the parameters to reduce
energy consumption. To the best of our knowledge, this problem is not solved
yet due to its challenging nature. The gap in the literature is due to the
advancements in the technology and drawbacks of the optimization algorithms and
the introduction of different new optimization algorithms. Further, many newly
proposed optimization algorithms which have produced better accuracy on the
benchmark instances but have not been applied yet for the optimization of
energy consumption in smart homes. In this paper, we have carried out a
detailed literature review of the techniques used for the optimization of
energy consumption and scheduling in smart homes. The detailed discussion has
been carried out on different factors contributing towards thermal comfort,
visual comfort, and air quality comfort. We have also reviewed the fog and edge
computing techniques used in smart homes
Human-Machine Communication: Complete Volume. Volume 2
This is the complete volume of HMC Volume 2
State Funded Research Annual Report FY09
The University of Maine System is required to submit in January of each year an annual report on the utilization of state research appropriations for operations and state research capital bonds. The report is to cover the most recently completed fiscal year
Innovating for efficiency: the use of generative AI in Kenyan newsrooms.
Generative AI has revolutionized media landscapes around the globe, including in Kenya. Widely known for mobile technology adoption and digital entrepreneurship, Kenya\u27s journalism field is experiencing drastic transformation thanks to AI\u27s powerful abilities. This study sought to understand how Generative AI (GenAI) is being adopted by Kenyan media houses, as well as its advantages, drawbacks, and challenges associated with journalistic innovation. Chapter 1 introduces the global impact of
Generative AI while outlining specific implications for Kenyan newsrooms. Contextualizing AI\u27s rise in media, this paper compares traditional and modern journalistic practices as well as big tech\u27s impact in shaping news consumption and distribution. This chapter introduces the research objectives, outlining AI\u27s current use in Kenya as well as barriers and opportunities related to adoption for journalists as well as differences between legacy media houses and digital media houses in their technological adoption strategies. Chapter 2 contains findings from interviews conducted with Kenyan news professionals regarding AI integration. Digital journalists, managing editors, and media personnel provide insights into how AI revolutionizes news production - from content generation to audience engagement. Chapter two addresses challenges related to technological change resistance and ethical concerns; opportunities presented by AI technology for journalistic practice enhancement; as well as training opportunities related to AI skills acquisition. Chapter 3 brings it all together by synthesizing insights and analyses associated with Generative AI\u27s impact on Kenyan journalism. It examines AI\u27s historical and contemporary uses in newsrooms, its integration challenges, and potential benefits for augmenting journalism. Furthermore, this chapter contrasts legacy media\u27s approaches toward adopting AI while emphasizing training support from management and training as key to successful implementation. This document concludes with strategic recommendations for effective AI integration, emphasizing ethical frameworks, localization for Kenyan contexts, and audience-centric AI development as essential requirements. Finally, the project document provides a step-by-step development process for a tool that leverages Generative AI technology in newsrooms for increased productivity and efficiency, in line with the needs presented through this study. Each step is unique in its own way
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