Planning And Scheduling For Large-scaledistributed Systems

Many applications require computing resources well beyond those available on any single system. Simulations of atomic and subatomic systems with application to material science, computations related to study of natural sciences, and computer-aided design are examples of applications that can benefit from the resource-rich environment provided by a large collection of autonomous systems interconnected by high-speed networks. To transform such a collection of systems into a user\u27s virtual machine, we have to develop new algorithms for coordination, planning, scheduling, resource discovery, and other functions that can be automated. Then we can develop societal services based upon these algorithms, which hide the complexity of the computing system for users. In this dissertation, we address the problem of planning and scheduling for large-scale distributed systems. We discuss a model of the system, analyze the need for planning, scheduling, and plan switching to cope with a dynamically changing environment, present algorithms for the three functions, report the simulation results to study the performance of the algorithms, and introduce an architecture for an intelligent large-scale distributed system

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

Gender differences in visuospatial planning: an eye movements study.

Gender studies report a male advantage in several visuospatial abilities. Only few studies however, have evaluated differences in visuospatial planning behaviour with regard to gender. This study was aimed at exploring whether gender may affect the choice of cognitive strategies in a visuospatial planning task and, if oculomotor measures could assist in disentangling the cognitive processes involved. A computerised task based on the travelling salesperson problem paradigm, the Maps test, was used to investigate these issues. Participants were required to optimise time and space of a path travelling among a set of sub-goals in a spatially constrained environment. Behavioural results suggest that there are no gender differences in the initial visual processing of the stimuli, but rather during the execution of the plan, with males showing a shorter execution time and a higher path length optimisation than females. Males often showed changes of heuristics during the execution while females seemed to prefer a constant strategy. Moreover, a better performance in behavioural and oculomotor measures seemed to suggest that males are more able than females in either the optimisation of spatial features or the realisation of the planned scheme. Despite inconclusive findings, the results support previous research and provide insight into the level of cognitive processing involved in navigation and planning tasks, with regard to the influence of gender

Recent Advances in General Game Playing

The goal of General Game Playing (GGP) has been to develop computer programs that can perform well across various game types. It is natural for human game players to transfer knowledge from games they already know how to play to other similar games. GGP research attempts to design systems that work well across different game types, including unknown new games. In this review, we present a survey of recent advances (2011 to 2014) in GGP for both traditional games and video games. It is notable that research on GGP has been expanding into modern video games. Monte-Carlo Tree Search and its enhancements have been the most influential techniques in GGP for both research domains. Additionally, international competitions have become important events that promote and increase GGP research. Recently, a video GGP competition was launched. In this survey, we review recent progress in the most challenging research areas of Artificial Intelligence (AI) related to universal game playing