Martin Beer

Work place: Sheffield Hallam University, Department of Computing, Sheffield, S1 1WB, United Kingdom



Research Interests: Computer Science & Information Technology, World Wide Web


Martin Beer has a PhD in Computational Chemistry. Until his retirement in 2017, he was a Principle Lecturer in the Department of computing, Sheffield Hallam University, UK. His research interest includes multi-agents, semantic web technology, and mobile learning. Dr. Beer is a Fellow of the BCS.

Author Articles
Formalizing Logic Based Rules for Skills Classification and Recommendation of Learning Materials

By Kennedy E Ehimwenma Paul Crowther Martin Beer

DOI:, Pub. Date: 8 Sep. 2018

First-order logic based data structure have knowledge representations in Prolog-like syntax. In an agent based system where beliefs or knowledge are in FOL ground fact notation, such representation can form the basis of agent beliefs and inter-agent communication. This paper presents a formal model of classification rules in first-order logic syntax. In the paper, we show how the conjunction of boolean [Passed, Failed] decision predicates are modelled as Passed(N) or Failed(N) formulas as well as their implementation as knowledge in agent oriented programming for the classification of students’ skills and recommendation of learning materials. The paper emphasizes logic based contextual reasoning for accurate diagnosis of students’ skills after a number of prior skills assessment. The essence is to ensure that students attain requisite skill competences before progressing to a higher level of learning.

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