The Story of Brother Ricardo’s Song

An account of how Charles Bud Thompson recorded the words and notes of a spirit song from Brother Ricardo Beldon, the last male member of the Hancock Shaker community and of the Hancock Bishopric. Includes transcription

Behavlets: a Method for Practical Player Modelling using Psychology-Based Player Traits and Domain Specific Features

As player demographics broaden it has become important to understand variation in player types. Improved player models can help game designers create games that accommodate a range of play styles/preferences, and may also facilitate the design of systems that detect player type and adapt dynamically in real-time. Existing approaches can model players, but most focus on tracking and classifying behaviour based on simple functional metrics such as deaths, specific choices, player avatar attributes, and completion times. We describe a different approach which seeks to leverage expert domain knowledge using a theoretical framework linking behaviour and game design patterns. The aim is to derive features of play from sequences of actions which are intrinsically informative about behaviour – which, because they are directly interpretable with respect to psychological theory of behaviour, we name ‘Behavlets’. We present the theoretical underpinning of this approach from research areas including psychology, temperament theory, player modelling, and game composition. The Behavlet creation process is described in detail; illustrated using a clone of the well-known game Pac-Man, with data gathered from 100 participants. A workshop evaluation study is also presented, where nine game design expert participants were briefed on the Behavlet concepts and requisite models, and then attempted to apply the method to games of the well-known first/third-person shooter genres, exemplified by ‘Gears of War’, (Microsoft). The participants found 139 Behavlet concepts mapping from behavioural preferences of the temperament types, to design patterns of the shooter genre games. We conclude that the Behavlet approach has significant promise, is complementary to existing methods and can improve theoretical validity of player models.Peer reviewe

Adaptive Artificial Intelligence in Games : Issues, Requirements, and a Solution through Behavlets-based General Player Modelling

8 pages, 1 figureWe present the last of a series of three academic essays which deal with the question of how and why to build a generalized player model. We propose that a general player model needs parameters for subjective experience of play, including: player psychology, game structure, and actions of play. Based on this proposition, we pose three linked research questions: RQ1 what is a necessary and sufficient foundation to a general player model?; RQ2 can such a foundation improve performance of a computational intelligence- based player model?; and RQ3 can such a player model improve efficacy of adaptive artificial intelligence in games? We set out the arguments behind these research questions in each of the three essays, presented as three preprints. The third essay, in this preprint, presents the argument that adaptive game artificial intelligence will be enhanced by a generalised player model. This is because games are inherently human artefacts which therefore, require some encoding of the human perspective in order to effectively autonomously respond to the individual player. The player model informs the necessary constraints on the adaptive artificial intelligence. A generalised player model is not only more efficient than a per-game solution, but also allows comparison between games which makes it a useful tool for studying play in general. We describe the concept and meaning of an adaptive game. We propose requirements for functional adaptive AI, arguing from first principles drawn from the games research literature. We propose solutions to these requirements, based on a formal model approach to our existing 'Behavlets' method for psychologically-derived player modelling: Cowley, B., & Charles, D. (2016). Behavlets: a Method for Practical Player Modelling using Psychology-Based Player Traits and Domain Specific Features. User Modeling and User-Adapted Interaction, 26(2), 257-306.Non peer reviewe

Arkansas Agricultural Chemical Ground-Water Management Plan

The Arkansas Agricultural Chemical Ground-Water Management Plan (SMP) is based on the Draft State Pesticide Ground- Water Management Plan Guidance and The Pesticides and Ground-Water Protection Strategy prepared by the U.S. Environmental Protection Agency (EPA). The need for a plan to protect ground water from contamination by agricultural chemicals and agents arises from evidence nationwide that using these chemicals can, in some instances, lead to contamination. In February 1988, EPA proposed a strategy to regulate certain pesticides by prohibiting their use in areas vulnerable to leaching unless a state develops and implements an acceptable management plan. The advantage of a state plan as opposed to a federal plan is that a state plan can provide protection for ground-water resources without unnecessarily restricting pesticide use. State plans can be more sensitive to local conditions such as soil types, farming practices and hydrogeological considerations

Economic impact of energy saving techniques in cloud server

In recent years, lot of research has been carried in the field of cloud computing and distributed systems to investigate and understand their performance. Economic impact of energy consumption is of major concern for major companies. Cloud Computing companies (Google, Yahoo, Gaikai, ONLIVE, Amazon and eBay) use large data centers which are comprised of virtual computers that are placed globally and require a lot of power cost to maintain. Demand for energy consumption is increasing day by day in IT firms. Therefore, Cloud Computing companies face challenges towards the economic impact in terms of power costs. Energy consumption is dependent upon several factors, e.g., service level agreement, virtual machine selection techniques, optimization policies, workload types etc. We address a solution for the energy saving problem by enabling dynamic voltage and frequency scaling technique for gaming data centers. The dynamic voltage and frequency scaling technique is compared against non-power aware and static threshold detection techniques. This helps service providers to meet the quality of service and quality of experience constraints by meeting service level agreements. The CloudSim platform is used for implementation of the scenario in which game traces are used as a workload for testing the technique. Selection of better techniques can help gaming servers to save energy cost and maintain a better quality of service for users placed globally. The novelty of the work provides an opportunity to investigate which technique behaves better, i.e., dynamic, static or non-power aware. The results demonstrate that less energy is consumed by implementing a dynamic voltage and frequency approach in comparison with static threshold consolidation or non-power aware technique. Therefore, more economical quality of services could be provided to the end users

Artificial Intelligence in Education as a Rawlsian Massively Multiplayer Game : A Thought Experiment on AI Ethics

In this chapter, we reflect on the deployment of AI as a pedagogical and educational instrument. When AI enters into classrooms, it becomes as a project with diverse members who have differing stakes, and it produces various socio-cognitive-technological questions that must be discussed. Furthermore, AI is developing fast and renders obsolete old paradigms for, e.g. data access, privacy, and transparency. AI may bring many positive consequences in schools — not only for individuals, or teachers, but for the educational system as a whole. On the other hand, there are also serious risks. Thus, the analysis of the educational uses of AI in future schools pushes us to compare the possible benefits (for example, using AI-based tools for supporting different learners) with the possible risks (for example, the danger of algorithmic manipulation, or a danger of hidden algorithmic discrimination). Practical solutions are many, for example the Solid protocol by Tim Berners-Lee, but are often conceived as solutions to single problems, with limited application. We describe a thought experiment: "education as a massively multiplayer social online game". Here, all actors (humans, institutions, AI agents and algorithms) are required to conform to the definition of a player: which is a role designed to maximise protection and benefit for human players. AI models that understand the game space provide an API for typical algorithms, e.g. deep learning neural nets or reinforcement learning agents, to interact with the game space. Our thought experiment clarifies the steep challenges, and also the opportunity, of AI in education.Peer reviewe

Utility of a Behavlets approach to a Decision theoretic predictive player model

6 pages, 3 figures, 1 tableWe present the second in a series of three academic essays which deal with the question of how to build a generalized player model. We begin with a proposition: a general model of players requires parameters for the subjective experience of play, including at least three areas: a) player psychology, b) game structure, and c) actions of play. Based on this proposition, we pose three linked research questions, which make incomplete progress toward a generalized player model: RQ1 what is a necessary and sufficient foundation to a general player model?; RQ2 can such a foundation improve performance of a computational intelligence-based player model?; and RQ3 can such a player model improve efficacy of adaptive artificial intelligence in games? We set out the arguments for each research question in each of the three essays, presented as three preprints. The second essay, in this preprint, illustrates how our 'Behavlets' method can improve the performance and accuracy of a predictive player model in the well-known Pac-Man game, by providing a simple foundation for areas a) to c) above. We then propose a plan for future work to address RQ2 by conclusively testing the Behavlets approach. This plan builds on the work proposed in the first preprint essay to address RQ1, and in turn provides support for work on RQ3. The Behavlets approach was described previously; therefore if citing this work please use the correct citation: Cowley B, Charles D. Behavlets: a Method for Practical Player Modelling using Psychology-Based Player Traits and Domain Specific Features. User Modelling and User-Adapted Interaction. 2016 Feb 8; online (Special Issue on Personality in Personalized Systems):150.Non peer reviewe