On Agent-Based Software Engineering

Agent-based computing represents an exciting new synthesis both for Artificial Intelligence (AI) and, more generally, Computer Science. It has the potential to significantly improve the theory and the practice of modeling, designing, and implementing computer systems. Yet, to date, there has been little systematic analysis of what makes the agent-based approach such an appealing and powerful computational model. Moreover, even less effort has been devoted to discussing the inherent disadvantages that stem from adopting an agent-oriented view. Here both sets of issues are explored. The standpoint of this analysis is the role of agent-based software in solving complex, real-world problems. In particular, it will be argued that the development of robust and scalable software systems requires autonomous agents that can complete their objectives while situated in a dynamic and uncertain environment, that can engage in rich, high-level social interactions, and that can operate within flexible organisational structures

Augmenting the field experience: a student-led comparison of techniques and technologies

In this study we report on our experiences of creating and running a student fieldtrip exercise which allowed students to compare a range of approaches to the design of technologies for augmenting landscape scenes. The main study site is around Keswick in the English Lake District, Cumbria, UK, an attractive upland environment popular with tourists and walkers. The aim of the exercise for the students was to assess the effectiveness of various forms of geographic information in augmenting real landscape scenes, as mediated through a range of techniques and technologies. These techniques were: computer-generated acetate overlays showing annotated wireframe views from certain key points; a custom-designed application running on a PDA; a mediascape running on the mScape software on a GPS-enabled mobile phone; Google Earth on a tablet PC; and a head-mounted in-field Virtual Reality system. Each group of students had all five techniques available to them, and were tasked with comparing them in the context of creating a visitor guide to the area centred on the field centre. Here we summarise their findings and reflect upon some of the broader research questions emerging from the project

Introduction to location-based mobile learning

[About the book] The report follows on from a 2-day workshop funded by the STELLAR Network of Excellence as part of their 2009 Alpine Rendez-Vous workshop series and is edited by Elizabeth Brown with a foreword from Mike Sharples. Contributors have provided examples of innovative and exciting research projects and practical applications for mobile learning in a location-sensitive setting, including the sharing of good practice and the key findings that have resulted from this work. There is also a debate about whether location-based and contextual learning results in shallower learning strategies and a section detailing the future challenges for location-based learning

Numerical Analysis

Acknowledgements: This article will appear in the forthcoming Princeton Companion to Mathematics, edited by Timothy Gowers with June Barrow-Green, to be published by Princeton University Press.\ud \ud In preparing this essay I have benefitted from the advice of many colleagues who corrected a number of errors of fact and emphasis. I have not always followed their advice, however, preferring as one friend put it, to "put my head above the parapet". So I must take full responsibility for errors and omissions here.\ud \ud With thanks to: Aurelio Arranz, Alexander Barnett, Carl de Boor, David Bindel, Jean-Marc Blanc, Mike Bochev, Folkmar Bornemann, Richard Brent, Martin Campbell-Kelly, Sam Clark, Tim Davis, Iain Duff, Stan Eisenstat, Don Estep, Janice Giudice, Gene Golub, Nick Gould, Tim Gowers, Anne Greenbaum, Leslie Greengard, Martin Gutknecht, Raphael Hauser, Des Higham, Nick Higham, Ilse Ipsen, Arieh Iserles, David Kincaid, Louis Komzsik, David Knezevic, Dirk Laurie, Randy LeVeque, Bill Morton, John C Nash, Michael Overton, Yoshio Oyanagi, Beresford Parlett, Linda Petzold, Bill Phillips, Mike Powell, Alex Prideaux, Siegfried Rump, Thomas Schmelzer, Thomas Sonar, Hans Stetter, Gil Strang, Endre Süli, Defeng Sun, Mike Sussman, Daniel Szyld, Garry Tee, Dmitry Vasilyev, Andy Wathen, Margaret Wright and Steve Wright

Theories, models, simulations: a computational challenge

In this talk I would like to illustrate with examples taken from Quantum Field Theory and Biophysics how an intelligent exploitation of the unprecedented power of today's computers could led not only to the solution of pivotal problems in the theory of Strong Interactions, but also to the emergence of new lines of interdisciplinary research, while at the same time pushing the limits of modeling to the realm of living systems.Comment: 19 pages, 1 figure, conference pape

A proposed study of multiple scattering through clouds up to 1 THz

A rigorous computation of the electromagnetic field scattered from an atmospheric liquid water cloud is proposed. The recent development of a fast recursive algorithm (Chew algorithm) for computing the fields scattered from numerous scatterers now makes a rigorous computation feasible. A method is presented for adapting this algorithm to a general case where there are an extremely large number of scatterers. It is also proposed to extend a new binary PAM channel coding technique (El-Khamy coding) to multiple levels with non-square pulse shapes. The Chew algorithm can be used to compute the transfer function of a cloud channel. Then the transfer function can be used to design an optimum El-Khamy code. In principle, these concepts can be applied directly to the realistic case of a time-varying cloud (adaptive channel coding and adaptive equalization). A brief review is included of some preliminary work on cloud dispersive effects on digital communication signals and on cloud liquid water spectra and correlations