Delivering services by building and running virtual organisations

Non peer reviewedPostprin

Narrative Generation in Entertainment: Using Artificial Intelligence Planning

From the field of artificial intelligence (AI) there is a growing stream of technology capable of being embedded in software that will reshape the way we interact with our environment in our everyday lives. This ‘AI software’ is often used to tackle more mundane tasks that are otherwise dangerous or meticulous for a human to accomplish. One particular area, explored in this paper, is for AI software to assist in supporting the enjoyable aspects of the lives of humans. Entertainment is one of these aspects, and often includes storytelling in some form no matter what the type of media, including television, films, video games, etc. This paper aims to explore the ability of AI software to automate the story-creation and story-telling process. This is part of the field of Automatic Narrative Generator (ANG), which aims to produce intuitive interfaces to support people (without any previous programming experience) to use tools to generate stories, based on their ideas of the kind of characters, intentions, events and spaces they want to be in the story. The paper includes details of such AI software created by the author that can be downloaded and used by the reader for this purpose. Applications of this kind of technology include the automatic generation of story lines for ‘soap operas’

Using motivation derived from computer gaming in the context of computer based instruction

This paper was originally presented at the IEEE Technically Sponsored SAI Computing Conference 2016, London, 13-15 July 2016. Abstract— this paper explores how to exploit game based motivation as a way to promote engagement in computer-based instruction, and in particular in online learning interaction. The paper explores the human psychology of gaming and how this can be applied to learning, the computer mechanics of media presentation, affordances and possibilities, and the emerging interaction of playing games and how this itself can provide a pedagogical scaffolding to learning. In doing so the paper focuses on four aspects of Game Based Motivation and how it may be used; (i) the game player’s perception; (ii) the game designers’ model of how to motivate; (iii) team aspects and social interaction as a motivating factor; (iv) psychological models of motivation. This includes the increasing social nature of computer interaction. The paper concludes with a manifesto for exploiting game based motivation in learning

Information Technology and Transport: What Research Needs to be Started Now?.

The ten week period from 9th October to 19th December 1982 was spent as Visiting Fellow at Leeds University at the Institute for Transport Studies; to examine the opportunities for research into the effects of information technology on transport and the interactions between them. This Fellowship was sponsored by the Science and Engineering Research Council (UK) and the Australian Road Research Board with additional support from Oxford Sytematics (Australia). This report reviews the scope for research in this area; with particular emphasis on identifying workable project directions in the Institute for Transport Studies (ITS). Appropriate contacts and related work are given. Topics covered include data acquisition systems (including the potential for hand-held data capture devices; and the use of aural, visual and micro-wave wavelengths in capturing data): data processing and comunications policy appropriate to the Institute' s requirements; the role of knowledge-based systems; and the analysis of the relation between communications and transport activities in respect of time-use and expenditure patterns. A number of the research proposals raised and put to ITS staff during the period are summarised in an Annex to this report (ITS technical Note TN 126). The summaries and texts of a series of seminars given during November-December 1982 at ITS are covered in a companion document (ITS Working Paper WP169)

A pragmatic approach to semantic repositories benchmarking

The aim of this paper is to benchmark various semantic repositories in order to evaluate their deployment in a commercial image retrieval and browsing application. We adopt a two-phase approach for evaluating the target semantic repositories: analytical parameters such as query language and reasoning support are used to select the pool of the target repositories, and practical parameters such as load and query response times are used to select the best match to application requirements. In addition to utilising a widely accepted benchmark for OWL repositories (UOBM), we also use a real-life dataset from the target application, which provides us with the opportunity of consolidating our findings. A distinctive advantage of this benchmarking study is that the essential requirements for the target system such as the semantic expressivity and data scalability are clearly defined, which allows us to claim contribution to the benchmarking methodology for this class of applications

Can a Self Assessement Tool for Environmental Controls which has been Informed by Users be of Benefit to Potential Users

This dissertation looks at the area of environmental control systems (ECS) also known as electronic aids for daily living for people with disabilities. These systems allow an individual with a disability to control devices such as a television, music player, telephone as well as a door, window or curtain controllers. A self-assessment tool was developed for potential users, which was informed by the feedback of (i) users who use or who have used environmental control systems, (ii) Enable Ireland staff who were involved in the service delivery of ECS and (iii) companies who install ECS for individuals with disabilities. These stakeholders were interviewed by a guided interview based on the research on assistive technology models. Results of interviews informed the self-assessment tool development. After the self-assessment tool was developed it was evaluated by potential users to see what benefits it had for potential users

Applying Formal Methods to Networking: Theory, Techniques and Applications

Despite its great importance, modern network infrastructure is remarkable for the lack of rigor in its engineering. The Internet which began as a research experiment was never designed to handle the users and applications it hosts today. The lack of formalization of the Internet architecture meant limited abstractions and modularity, especially for the control and management planes, thus requiring for every new need a new protocol built from scratch. This led to an unwieldy ossified Internet architecture resistant to any attempts at formal verification, and an Internet culture where expediency and pragmatism are favored over formal correctness. Fortunately, recent work in the space of clean slate Internet design---especially, the software defined networking (SDN) paradigm---offers the Internet community another chance to develop the right kind of architecture and abstractions. This has also led to a great resurgence in interest of applying formal methods to specification, verification, and synthesis of networking protocols and applications. In this paper, we present a self-contained tutorial of the formidable amount of work that has been done in formal methods, and present a survey of its applications to networking.Comment: 30 pages, submitted to IEEE Communications Surveys and Tutorial

Collaborative hybrid agent provision of learner needs using ontology based semantic technology

© Springer International Publishing AG 2017. This paper describes the use of Intelligent Agents and Ontologies to implement knowledge navigation and learner choice when interacting with complex information locations. The paper is in two parts: the first looks at how Agent Based Semantic Technology can be used to give users a more personalised experience as an individual. The paper then looks to generalise this technology to allow users to work with agents in hybrid group scenarios. In the context of University Learners, the paper outlines how we employ an Ontology of Student Characteristics to personalise information retrieval specifically suited to an individual’s needs. Choice is not a simple “show me your hand and make me a match” but a deliberative artificial intelligence (AI) that uses an ontologically informed agent society to consider the weighted solution paths before choosing the appropriate best. The aim is to enrich the student experience and significantly re-route the student’s journey. The paper uses knowledge-level interoperation of agents to personalise the learning space of students and deliver to them the information and knowledge to suite them best. The aim is to personalise their learning in the presentation/format that is most appropriate for their needs. The paper then generalises this Semantic Technology Framework using shared vocabulary libraries that enable individuals to work in groups with other agents, which might be other people or actually be AIs. The task they undertake is a formal assessment but the interaction mode is one of informal collaboration. Pedagogically this addresses issues of ensuring fairness between students since we can ensure each has the same experience (as provided by the same set of Agents) as each other and an individual mark may be gained. This is achieved by forming a hybrid group of learner and AI Software Agents. Different agent architectures are discussed and a worked example presented. The work here thus aims at fulfilling the student’s needs both in the context of matching their needs but also in allowing them to work in an Agent Based Synthetic Group. This in turn opens us new areas of potential collaborative technology

Time-Dependent Performance Prediction System for Early Insight in Learning Trends

Performance prediction systems allow knowing the learning status of students during a term and produce estimations on future status, what is invaluable information for teachers. The majority of current systems statically classify students once in time and show results in simple visual modes. This paper presents an innovative system with progressive, time-dependent and probabilistic performance predictions. The system produces by-weekly probabilistic classifications of students in three groups: high, medium or low performance. The system is empirically tested and data is gathered, analysed and presented. Predictions are shown as point graphs over time, along with calculated learning trends. Summary blocks are with latest predictions and trends are also provided for teacher efficiency. Moreover, some methods for selecting best moments for teacher intervention are derived from predictions. Evidence gathered shows potential to give teachers insights on students' learning trends, early diagnose learning status and selecting best moment for intervention