34188181
Literacy and Numeracy Edutainment Packages for Disaffected Young Learners
The UK Government has conducted research into skills gaps within the UK population. It has concluded that there is an alarmingly large proportion of the population with low literacy and numeracy skills.
31990272
Online Gardening to Promote Social Inclusion
There are several European initiatives aimed at producing rehabilitation and associated technologies, in response to a strong North American market created through Disability Act Legislation [1]. In the past we have developed projects that provide vocationally based work tutors to teach a range of horticulture, IT, catering and soft skills. These projects include the provision of virtual reality and multimedia based materials to develop the first of these vocational skills - horticulture.
44788901
Parallel genetic algorithms with local search
This paper presents methods of applying local search to global optimization problems. The most common approach, multistart, selects the best solution from restarts of local search from random starting points. Partitional methods augment local search with general principles concerning the location of global optima in real space, significantly improving the effectiveness of local search in function optimization problems. Standard partitional methods, however, are not directly applicable to combinatorial optimization problems. We describe a genetic algorithm, GALO, that is similar to the partitional methods, but can be applied to combinatorial problems. Empirical results are presented for a parallel implementation of GALO that show it to be effective for the quadratic assignment problem.
8868489
Design Simplification by Analogical Reasoning
This paper presents our research on design simplification by analogical reasoning. It defines a “simplification problem”, then describes our approach to solving design simplification problems by analogical reasoning. One of the important contributions of the research is the use of relevance for guiding the analogical reasoning process. Its benefits are analyzed using a set of experiments. Finally, the paper draws conclusions and proposes directions for future research
33879094
Defining configuring
This paper is intended to serve as part of the context in which the other papers in this special issue should be read. Its main goal is to revisit the basic definition of the configuration task, on which many people depend, to show some of its flaws, and to point out how it shapes thinking about the problem. We are concerned about characterizing the reasoning processes used to produce a configuration.
33488472
Expert System Assisted Test Data Generation for Software Branch Coverage
Abstract With the increased production of complex software systems, verification and validation (V & V) has evolved into a set of activities that span the entire software life cycle. Among these various activities, software testing plays a major role in V&V. Conventional software testing methods generally require considerable manual effort which can generate only a limited number of test cases before the amount of time expended becomes unacceptably large. In this paper, we present a new approach to generating test cases based on artificial intelligence methods. By analyzing the branch coverage of previous test cases, an expert system is able to generate new test cases which provide additional coverage. Heuristic rules are used to modify previous test cases in order to achieve the desired branch coverage. This approach to software testing has the potential for greatly reducing the overall costs associated with branch coverage testing.
18346977
Expectation-based Learning in Design
Design problems typically have a very large number of problem states, many of which cannot be anticipated at the onset of the design. Some design problem states are characterized by as many as hundreds of parameters. Given these amounts of uncertainty and information, AI design systems faced with learning tasks cannot know from the beginning what needs to be learned, and whether these needs will remain the same. In this abstract we describe how LEAD (Learning Expectations in Agent-based Design), a multiagent system for parametric and configuration design, addresses these challenges in design learning.