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Professor John McCall


Exploring aspects of cell intelligence with artificial reaction networks. (2013)
Journal Article
GERRARD, C. E., MCCALL, J., COGHILL, G. M. and MACLEOD, C. 2014. Exploring aspects of cell intelligence with artificial reaction networks. Soft computing [online], 18(10), pages 1899-1912. Available from: https://doi.org/10.1007/s00500-013-1174-8

The Artificial Reaction Network (ARN) is a Cell Signalling Network inspired connectionist representation belonging to the branch of A-Life known as Artificial Chemistry. Its purpose is to represent chemical circuitry and to explore computational prop... Read More about Exploring aspects of cell intelligence with artificial reaction networks..

Combining biochemical network motifs within an ARN-agent control system. (2013)
Conference Proceeding
GERRARD, C.E., MCCALL, J., MACLEOD, C. and COGHILL, G.M. 2013. Combining biochemical network motifs within an ARN-agent control system. In Jin, Y. and Thomas, S.A. (eds.) Proceedings of the 13th UK workshop on computational intelligence (UKCI 2013), 9-11 September 2013, Guildford, UK. New York: IEEE [online], article number 6651281, pages 8-15. Available from: https://doi.org/10.1109/UKCI.2013.6651281

The Artificial Reaction Network (ARN) is an Artificial Chemistry representation inspired by cell signaling networks. The ARN has previously been applied to the simulation of the chemotaxis pathway of Escherichia coli and to the control of limbed robo... Read More about Combining biochemical network motifs within an ARN-agent control system..

Partial structure learning by subset Walsh transform. (2013)
Conference Proceeding
CHRISTIE, L.A., LONIE, D.P. and MCCALL, J.A.W. 2013. Partial structure learning by subset Walsh transform. In Jin, Y. and Thomas, S.A. (eds.) Proceedings of the 13th UK workshop on computational intelligence (UKCI 2013), 9-11 September 2013, Guildford, UK. New York: IEEE [online], article number 6651297, pages 128-135. Available from: https://doi.org/10.1109/UKCI.2013.6651297

Estimation of distribution algorithms (EDAs) use structure learning to build a statistical model of good solutions discovered so far, in an effort to discover better solutions. The non-zero coefficients of the Walsh transform produce a hypergraph rep... Read More about Partial structure learning by subset Walsh transform..

Artificial chemistry approach to exploring search spaces using artificial reaction network agents. (2013)
Conference Proceeding
GERRARD, C.E., MCCALL, J., MACLEOD, C. and COGHILL, G.M. 2013. Artificial chemistry approach to exploring search spaces using artificial reaction network agents. In Proceedings of the 2013 IEEE congress on evolutionary computation (CEC 2013), 20-23 June 2013, Cancun, Mexico. New York: IEEE [online], article number 6557702, pages 1201-1208. Available from: https://doi.org/10.1109/CEC.2013.6557702

The Artificial Reaction Network (ARN) is a cell signaling network inspired representation belonging to the branch of A-Life known as Artificial Chemistry. It has properties in common with both AI and Systems Biology techniques including Artificial Ne... Read More about Artificial chemistry approach to exploring search spaces using artificial reaction network agents..

Bayesian network structure learning using characteristic properties of permutation representations with applications to prostate cancer treatment. (2013)
Thesis
REGNIER-COUDERT, O. 2013. Bayesian network structure learning using characteristic properties of permutation representations with applications to prostate cancer treatment. Robert Gordon University, PhD thesis.

Over the last decades, Bayesian Networks (BNs) have become an increasingly popular technique to model data under presence of uncertainty. BNs are probabilistic models that represent relationships between variables by means of a node structure and a s... Read More about Bayesian network structure learning using characteristic properties of permutation representations with applications to prostate cancer treatment..

Experimental user interface design toolkit for interaction research (IDTR). (2013)
Thesis
GOLOVINE, J.C.R.R. 2013. Experimental user interface design toolkit for interaction research (IDTR). Robert Gordon University, PhD thesis.

The research reported and discussed in this thesis represents a novel approach to User Interface evaluation and optimisation through cognitive modelling. This is achieved through the development and testing of a toolkit or platform titled Toolkit for... Read More about Experimental user interface design toolkit for interaction research (IDTR)..

Probabilistic modelling of oil rig drilling operations for business decision support: a real world application of Bayesian networks and computational intelligence. (2013)
Thesis
FOURNIER, F.A. 2013. Probabilistic modelling of oil rig drilling operations for business decision support: a real world application of Bayesian networks and computational intelligence. Robert Gordon University [online], PhD thesis. Available from: https://openair.rgu.ac.uk

This work investigates the use of evolved Bayesian networks learning algorithms based on computational intelligence meta-heuristic algorithms. These algorithms are applied to a new domain provided by the exclusive data, available to this project from... Read More about Probabilistic modelling of oil rig drilling operations for business decision support: a real world application of Bayesian networks and computational intelligence..

Approximating true relevance model in relevance feedback. (2013)
Thesis
ZHANG, P. 2013. Approximating true relevance model in relevance feedback. Robert Gordon University, PhD thesis.

Relevance is an essential concept in information retrieval (IR) and relevance estimation is a fundamental IR task. It involves not only document relevance estimation, but also estimation of user's information need. Relevance-based language model aims... Read More about Approximating true relevance model in relevance feedback..

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