The first day of the conference comprises a range of workshops, to be held on Monday 11th December. Delegates will find these events to be especially valuable where there is a current need to consider the introduction of new AI technologies into their own organisations.
There are expected to be six half-day workshops plus an all-day workshop (the Eleventh UK CBR Workshop). Delegates are free to choose any combination of morning and afternoon sessions to attend. The provisional programme of workshops is shown below. Note that the morning session starts at 11 a.m. (later than in previous years) to reduce the need for delegates to stay in Cambridge on Sunday night. There is a lunch break from 12.30-13.30 and there are refreshment breaks from 14.45-15.15 and from 16.30-17.00.
Intelligent Systems in Accounting, Finance and
Chair: Dr Bob Berry, University of Nottingham
The idea that intelligent systems have the potential to support the activities of managers in organisations has been around for a long time, and at first sight there is considerable evidence of that potential being realised. However, closer examination suggests that the engagement of intelligent systems researchers and practitioners with managers and management researchers is very limited. Examination of the intelligent systems literature suggests that many papers demonstrate the ability of a technique to handle a problem without considering either the importance of the problem or the issue of whether the technique adds value in any sense. Examination of the management journals and discussion with managers strongly suggests that intelligent systems are not relevant; they simply don't feature. The workshop aims to identify the important management problems and the intelligent systems approaches most likely to add value. The aim is to create a research agenda which will lead to the integration of intelligent systems into the practice of management and management research.
Artificial Intelligence in Education
Chair: Dr Maria Fasli, University of Essex
Artificial Intelligence (AI) has been incorporated into the curriculum of Computer Science degree schemes for a number of years now at both undergraduate and postgraduate levels. Despite the fact that the underlying research areas have developed over the years, teaching artificial intelligence and related topics presents a number of problems such as a heavy influence of one's own research expertise and specialization in deciding the content of such courses and a lack of standard methodologies and tools that practitioners can employ for teaching topics in this area. The aim of this workshop is to bring together researchers and practitioners that are interested in the teaching aspect of the field. The workshop will address issues specific to teaching AI including innovative approaches to learning and teaching AI, approaches for improving the students' learning experience, the integration of theory and practice and tools for supporting teaching and learning. The workshop will be a mixture of presentations and open discussions of the attendees.
Chair: Dr Tony Hirst, The Open University
There are many misconceptions in the public mind about the capabilities of artificial intelligence in general and intelligent robots in particular. As intelligent behaviours become embedded in everyday equipment, there is an increasing need to understand the huge potential of these new technologies, as well as their limitations. This workshop will review not only the latest developments in intelligent robotics and promote discussion of the challenges they present, but also question the desirability of research into different application areas and review public concerns regarding the quest to create 'conscious' robots.
AI in Recommender Systems
Chair: Dr Gulden Uchyigit, Imperial College London
Over the past decade recommender systems have evolved as specialised tools for helping users cope with information overload. AI has played a significant role in the development of these systems to provide more intelligent and personalised services. With today’s increasing information-overload problem, the area of recommender systems research is more challenging than ever before and the use of AI techniques is more popular than ever before. The aim of this workshop is to bring together researchers and practitioners that are interested in the application of AI techniques in the field of recommender systems research. The workshop will be a mixture of presentations and open discussions among the attendees.
Basics of AI - Part 1
Chair: Prof Adrian Hopgood, Nottingham Trent University
This workshop will provide an overview of principal topics in artificial intelligence. It will be of value to anyone who is new to the area. It will also be of equal value to anyone who has experience of specific aspects of AI but wishes to have a broader-based understanding. Part 1 will concentrate on symbolic representations of AI:
• Rule-based systems
• Case-based reasoning
• Semantic web
Basics of AI - Part 2
Chair: Prof Adrian Hopgood, Nottingham Trent University
Continuing the themes of Part 1, the second part of this workshop will concentrate
on data-based and numerical representations of AI. It will finish with an overview
of how the techniques presented in both sessions can be used cooperatively in
hybrid systems. Part 2 will, therefore, cover the following topics:
• Data mining
• Genetic algorithms
• Neural nets
Eleventh UK Case-Based Reasoning Workshop
Chair: Dr. Miltos Petridis, University of Greenwich, UK
Call for Papers