Pass the Ball: Enforced Turn-Taking in Activity Tracking

We have developed a mobile application called Pass The Ball that enables users to track, reflect on, and discuss physical activity with others. We followed an iterative design process, trialling a first version of the app with 20 people and a second version with 31. The trials were conducted in the wild, on users' own devices. The second version of the app enforced a turn-taking system that meant only one member of a group of users could track their activity at any one time. This constrained tracking at the individual level, but more successfully led users to communicate and interact with each other. We discuss the second trial with reference to two concepts: social-relatedness and individual-competence. We discuss six key lessons from the trial, and identify two high-level design implications: attend to "practices" of tracking; and look within and beyond "collaboration" and "competition" in the design of activity trackers

Virtual Reality Games for Motor Rehabilitation

This paper presents a fuzzy logic based method to track user satisfaction without the need for devices to monitor users physiological conditions. User satisfaction is the key to any product’s acceptance; computer applications and video games provide a unique opportunity to provide a tailored environment for each user to better suit their needs. We have implemented a non-adaptive fuzzy logic model of emotion, based on the emotional component of the Fuzzy Logic Adaptive Model of Emotion (FLAME) proposed by El-Nasr, to estimate player emotion in UnrealTournament 2004. In this paper we describe the implementation of this system and present the results of one of several play tests. Our research contradicts the current literature that suggests physiological measurements are needed. We show that it is possible to use a software only method to estimate user emotion

Emergence of self-similarity in football dynamics

The multiplayer dynamics of a football game is analyzed to unveil self-similarities in the time evolution of player and ball positioning. Temporal fluctuations in both the team-turf boundary and the ball location are uncovered to follow the rules of fractional Brownian motion with a Hurst exponent of H=0.7. The persistence time below which self-similarity holds is found to be several tens of seconds, implying a characteristic time scale that governs far-from-equilibrium motion on a playing field.Comment: Figures 1 and 2 are blurred due to file-size restriction. Sharply-defined images can be viewed in the final version published by European Physical Journal

Behavior Trees in Robotics and AI: An Introduction

A Behavior Tree (BT) is a way to structure the switching between different tasks in an autonomous agent, such as a robot or a virtual entity in a computer game. BTs are a very efficient way of creating complex systems that are both modular and reactive. These properties are crucial in many applications, which has led to the spread of BT from computer game programming to many branches of AI and Robotics. In this book, we will first give an introduction to BTs, then we describe how BTs relate to, and in many cases generalize, earlier switching structures. These ideas are then used as a foundation for a set of efficient and easy to use design principles. Properties such as safety, robustness, and efficiency are important for an autonomous system, and we describe a set of tools for formally analyzing these using a state space description of BTs. With the new analysis tools, we can formalize the descriptions of how BTs generalize earlier approaches. We also show the use of BTs in automated planning and machine learning. Finally, we describe an extended set of tools to capture the behavior of Stochastic BTs, where the outcomes of actions are described by probabilities. These tools enable the computation of both success probabilities and time to completion

Time to start training: A review of cognitive research in sport and proposal for bridging the gap from academia to the field

Research demonstrates the importance of perceptual-cognitive skills, such as pattern matching, anticipation, and decision making in numerous sports, including badminton (Abernethy & Russell, 1987), baseball (Burroughs, 1984), basketball (Allard, Graham, & Paarsalu, 1980), handball (Johnson & Raab, 2003), rugby (Lorains, Ball, & MacMahon, 2013), soccer (Ward & Williams, 2003), squash (Abernethy, 1990), tennis (Haskins, 1965), and volleyball (Borgeaud & Abernethy, 1987). While other factors may be important (e.g., visual search patterns), the accuracy and/or speed with which athletes anticipate their opponent’s intentions and/or decide on an appropriate course of action, as assessed in domain-specific tests designed to simulate and represent real-world sporting demands have been shown to be the best and most reliable predictors of skilled performance in the field (see Mann, Williams, Ward, & Janelle, 2007). Moreover, several studies indicate that when training is based on expert models of superior performance, these skills can be improved and transfer to the field (e.g., Fadde, 2009; Ward, Suss, & Basevitch, 2009). In most elite and everyday sports training contexts, expensive research technology (such as eye-tracking equipment) is not always available to practitioners that would help us better understand the cognitive basis of, and ecological constraints of anticipation and decision-making in a way that could be leveraged to tailor training to improve individual and team performance. However, other technologies are now becoming more readily available to support the development of perceptual-cognitive skills. This is particularly timely, because although there is a growing body of research demonstrating the trainability of perceptual-cognitive skills in sport and their transfer to the field, few researchers have attempted to translate this research into accessible and useful training tools for everyday coaches and athletes (for an example, see Belling, Suss, & Ward, 2014). Moreover, research on the validation of such perceptual-cognitive or decision-making skill training tools is startlingly absent from the literature, not just from research on human factors in sport, but in human factors more broadly. In this research, we review what has worked in the past, what can be leveraged by simple and effective tools for accessible devices (e.g., personal computer, tablet), and how powerful these tools can be by reviewing changes in real world performance following their implementation. An NCAA Division 1 baseball team was given access to Axon Sports Cognitive Training for hitting in baseball for the 2013 season. Batting statistics are compared from the 2012 season, without training present, and 2013 season, with training present. The results suggest that batting improved during the season when cognitive training was available to the players. Implications for future research and application are discussed

Agents for educational games and simulations

This book consists mainly of revised papers that were presented at the Agents for Educational Games and Simulation (AEGS) workshop held on May 2, 2011, as part of the Autonomous Agents and MultiAgent Systems (AAMAS) conference in Taipei, Taiwan. The 12 full papers presented were carefully reviewed and selected from various submissions. The papers are organized topical sections on middleware applications, dialogues and learning, adaption and convergence, and agent applications

Spartan Daily, October 18, 1993

Volume 101, Issue 35https://scholarworks.sjsu.edu/spartandaily/8463/thumbnail.jp