Journal Articles

  1. Z. Mahmood, D. Bowes, T. Hall, P.C.R. Lane and J. Petric, ‘Reproducibility and replicability of software defect prediction studies,’ Information and Software Technology, 99:148-63, 2018. Web page.
  2. D. Panday, R.C. de Amorim and P.C.R. Lane, ‘Feature weighting as a tool for unsupervised feature selection’, Information Processing Letters, 129:44-52, 2018. Web page.
  3. M. Lloyd-Kelly, F. Gobet and P.C.R. Lane, ‘A question of balance: The benefits of pattern-recognition when solving problems in a complex domain,’ LNCS Transactions on Computational Collective Intelligence XX, pp.224-258, 2015.
  4. P.C.R. Lane and F. Gobet, ‘Evolving non-dominated parameter sets for computational models from multiple experiments’, Journal of Artificial General Intelligence, 4:1-30, 2013. Web page.
  5. P.C.R. Lane and F. Gobet, ‘A theory-driven testing methodology for developing scientific software’, Journal of Experimental and Theoretical Artificial Intelligence, 24:421-56, 2012. Web page.
  6. P.C.R. Lane, D. Clarke, and P. Hender, ‘On developing robust models for favourability analysis: Model choice, feature sets and imbalanced data,’ Decision Support Systems, 53:712-18, 2012. Web page.
  7. P.C.R. Lane and F. Gobet, ‘Perception in chess and beyond: Commentary on Linhares and Freitas (2010)‘, New Ideas in Psychology, 29:156-61, 2011. Web page.
  8. A.A. Albrecht, P.C.R. Lane and K. Steinhöfel, ‘Analysis of local search landscapes for k-SAT instances,’ Mathematics in Computer Science, 3:465-488, 2010. Web page.
  9. J.P. Bao, C.M. Lyon and P.C.R. Lane, ‘Copy detection in Chinese documents using Ferret,’ Language Resources and Evaluation, 40:357-365, 2006. Web page.
  10. P.C.R. Lane and F.Gobet, ‘Developing reproducible and comprehensible computational models,’ Artificial Intelligence, 144:251-263, 2003. Web page.
  11. P.C.R. Lane and J.B. Henderson, ‘Towards effective parsing with neural networks: Inherent generalisations and bounded resource effects,’ Applied Intelligence, 19:83-100, 2003. Web page.
  12. F. Gobet, P.C.R. Lane, S. Croker, P.C-H. Cheng, G. Jones, I. Oliver, and J.M. Pine, ‘Chunking mechanisms in human learning,’ Trends in Cognitive Sciences, 5:236-243, 2001. Web page.
  13. P.C.R. Lane and J.B. Henderson, ‘Incremental syntactic parsing of natural language corpora with Simple Synchrony Networks,’ IEEE Transactions on Knowledge and Data Engineering, 13:219-231, 2001. Web page.
  14. P.C.R. Lane, P.C-H. Cheng and F. Gobet, ‘CHREST+: Investigating how humans learn to solve problems with diagrams,’ AISB Quarterly, 103:24-30, 2000.

Refereed Conference Papers

  1. F. Gobet and P.C.R. Lane, ‘Constructing a standard model: Lessons from CHREST’, in Proceedings of the AAAI Fall Symposium on A Standard Model of the Mind, 2017. Web page
  2. M. Lloyd-Kelly, F. Gobet and P.C.R. Lane, ‘Under pressure: How time-limited cognition explains statistical learning by 8-month old infants’, in Papafragou, A., Grodner, D., Mirman, D., and Trueswell, J.C. (Eds.), Proceedings of the 38th Annual Meeting of the Cognitive Science Society, pp.1475-80, 2016.
  3. P.C.R. Lane, P.D. Sozou, F. Gobet and M. Addis, ‘Analysing psychological data by evolving computational models’, in A. Wilhelm and H. Kestler (Eds.), Analysis of Large and Complex Data, Springer, pp.587-597, 2016. [Proceedings of the European Conference on Data Analysis 2014]. Web page.
  4. M. Addis, P.D. Sozou, P.C.R. Lane and F. Gobet, ‘Computational scientific discovery and cognitive science theories’, in Müller, Vincent C. (ed.), Computing and Philosophy: Selected papers from IACAP 2014, Heidelberg: Springer (Synthese Library), 2016. Web page.
  5. M. Lloyd-Kelly, F. Gobet and P.C.R. Lane, ‘Piece of mind: Long-term memory structure in ACT-R and CHREST’, in Noelle, D. C., Dale, R., Warlaumont, A. S., Yoshimi, J., Matlock, T., Jennings, C. D., & Maglio, P. P. (Eds.), Proceedings of the 37th Annual Meeting of the Cognitive Science Society, (Austin, TX: Cognitive Science Society) pp.1422-27, 2015. Web page.
  6. M. Lloyd-Kelly, F. Gobet and P.C.R. Lane, ‘The art of balance: Problem-solving vs pattern-recognition,’ in Proceedings of the Seventh International Conference on Agents and Artificial Intelligence, 2015.
  7. Z. Mahmood, D. Bowes, P.C.R. Lane and T. Hall, ‘What is the impact of imbalance on software defect prediction performance?’, in Proceedings of the 11th International Conference on Predictive Models and Data Analytics in Software Engineering (PROMISE 2015), 2015.
  8. M. Lloyd-Kelly, P.C.R. Lane and F. Gobet, ‘The effects of bounding rationality on the performance and learning of CHREST agents in Tileworld’, in M.Bramer and M.Petridis (Eds.) Research and Development in Intelligent Systems XXXI: Proceedings of AI-2014, The Thirty-Fourth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp.149-162, 2014. (London, UK: Springer-Verlag)
  9. P.C.R. Lane, P.D. Sozou, M. Addis and F. Gobet, ‘Evolving process-based models from psychological data using genetic programming’, in Rodger Kibble (ed.) Proceedings of the 50th Anniversary Convention of the AISB, 2014.
  10. P.C.R. Lane and F. Gobet, ‘CHREST models of implicit learning and board game interpretation’, in J.Bach, B.Goertzel and M.Ikle (Eds.), Proceedings of the Fifth Conference on Artificial General Intelligence, LNAI 7716, pp. 148-157, 2012. (Berlin, Heidelberg: Springer-Verlag) Download.
  11. P.C.R. Lane and F. Gobet, ‘Using chunks to categorise chess positions’, in M.Bramer and M.Petridis (Eds.) Research and Development in Intelligent Systems XXX: Proceedings of AI-2012, The Thirty-Second SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 93-106, 2012. (London, UK: Springer-Verlag)
  12. T. Bossomaier, J. Traish, F. Gobet and P.C.R. Lane, ‘Neuro-cognitive model of move location in the game of Go’, in the 2012 International Joint Conference on Neural Networks (IJCNN 2012). Web page.
  13. P.D. Green, P.C.R. Lane, A.W. Rainer, S. Scholz, and S.J. Bennett, ‘Same difference: Detecting collusion by finding unusual shared elements’, in Proceedings of the Fifth International Plagiarism Conference, 2012.
  14. D. Clarke, P.C.R. Lane and P. Hender, ‘Semi-automatic analysis of traditional media with machine learning’, in M. Bramer, M. Petridis and L. Nolle (Eds.), Research and Development in Intelligent Systems XXVIII: Proceedings of AI-2011, The Thirty-First SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 325-37, 2011. (London, UK: Springer-Verlag)
  15. D. Clarke, P.C.R. Lane and P. Hender, ‘Developing robust models for favourability analysis’, in A. Balahur, E. Boldrini, A. Montoyo and P. Martinez-Barco (Eds.), Second Workshop on Computational Approaches to Subjectivity and Sentiment Analysis (WASSA), pp.44-52, Association for Computational Linguistics, Portland, Oregon, 2011.
  16. P.D. Green, P.C.R. Lane, A.W. Rainer and S. Scholz, ‘Selecting features in origin analysis’, in M. Bramer, M. Petridis and A. Hopgood (Eds.) Research and Development in Intelligent Systems XXVII: Proceedings of AI-2010, The Thirtieth SGAI International Conference on Innovative Techniques and Applications of Artificial Intelligence, pp. 379-392, 2011. (London, UK: Springer-Verlag)
  17. F. Gobet and P.C.R. Lane, ‘The CHREST architecture of cognition: The role of perception in general intelligence’, in M. Hutter, E.B. Baum and E. Kitzelmann (Eds). Proceedings of the Third conference on Artificial General Intelligence, pp. 7-12, 2010. (Paris, France: Atlantis Press)
  18. J.W. Han, P.C.R. Lane, N. Davey and Y. Sun, ‘Attention mechanisms and component-based face detection’, in Proceedings of the International Conference on Methods and Models in Computer Science (IEEE Computer Society), pp. 57-62, 2009. Web page.
  19. J.A. Malcolm and P.C.R. Lane, ‘Tackling the PAN’09 external plagiarism detection corpus with a desktop plagiarism detector’, in Proceedings of the 3rd PAN Workshop “Uncovering Plagiarism, Authorship and Social Software Misuse”, pp.29-33, 2009.
  20. R. Ll. Smith, F. Gobet and P.C.R. Lane, ‘Checking chess checks with chunks: A model of simple check detection’, in A. Howes, D. Peebles, R. Cooper (Eds.), Proceedings of the Ninth International Conference on Cognitive Modelling, 2009.
  21. P.D. Green, P.C.R. Lane, A.W. Rainer and S. Scholz, ‘Building classifiers to identify split files’, in Proceedings of the International Conference on Machine Learning and Data Mining, 2009.
  22. P.C.R. Lane, F. Gobet and R. Ll. Smith, ‘Attention mechanisms in the CHREST cognitive architecture’, in L. Paletta and J. K. Tsotsos (eds), Proceedings of the Fifth International Workshop on Attention in Cognitive Systems, (Springer-Verlag) LNCS 5395, pp. 183-196, 2009.
  23. A.W. Rainer, P.C.R. Lane, J.A. Malcolm and S. Scholz, ‘Using n-grams to rapidly characterise the evolution of software code’, in Proceedings of the Fourth International ERCIM Workshop on Software Evolution and Evolvability (IEEE Computer Society), pp.43-52, 2008.
  24. R. Ll. Smith, P.C.R. Lane and F. Gobet, ‘Modelling the relationship between visual short-term memory capacity and recall ability’, in The Second UKSim European Symposium on Computer Modelling and Simulation (IEEE Computer Society), pp. 99-104, 2008.
  25. J.A. Malcolm and P.C.R. Lane, ‘An approach to detecting article spinning’, in Proceedings of the Third International Conference on Plagiarism, 2008.
  26. A. Albrecht, P.C.R. Lane and K. Steinhöfel, ‘Combinatorial landscape analysis for k-SAT instances’, in Proceedings of the IEEE Congress on Evolutionary Computation, pp.2498-2504, 2008. Web page.
  27. J.A. Malcolm and P.C.R. Lane, ‘Efficient search for plagiarism on the web’, in Proceedings of the International Conference on Technology, Communication and Education, pp. 206-211, 2008.
  28. P.C.R. Lane and F. Gobet, ‘A methodology for developing computational implementations of scientific theories’, Proceedings of the Tenth International Conference on Computer Modelling & Simulation (IEEE Computer Society), pp. 392-7, 2008. Web page.
  29. A. Albrecht, P.C.R. Lane and K. Steinhöfel, ‘Estimating the number of local maxima for k-SAT Instances’, in Proceedings of the Tenth International Symposium on Artificial Intelligence and Mathematics (ISAIM 2008), 2008.
  30. J.W. Han, P.C.R. Lane, N. Davey and Y. Sun, ‘Comparing the performance of single-layer and two-layer support vector machines on face detection’, in Proceedings of The Seventh UK Workshop on Computational Intelligence, 2007.
  31. R. Ll. Smith, F. Gobet and P.C.R. Lane, ‘An investigation into the effect of ageing on expert memory with CHREST’, in Proceedings of The Seventh UK Workshop on Computational Intelligence, 2007.
  32. P.C.R. Lane and F. Gobet, ‘Developing and evaluating cognitive architectures with behavioural tests’, in Workshop on Evaluating Architectures for Intelligence, at the Twenty-Second Conference on Artificial Intelligence (AAAI-2007), 2007. Web page.
  33. J.P. Bao, C.M. Lyon and P.C.R. Lane, ‘A text annotation method based on semantic sequence’, in Proceedings of the Seventh International Workshop on Computational Semantics, 2007.
  34. J.W. Han, P.C.R. Lane, N. Davey, Y. Sun, ‘A dual-layer model of high-level perception’, in R.M. French and E. Thomas (eds.), From Associations to Rules: Connectionist Models of Behavior and Cognition, Proceedings of the Tenth Neural Computation and Psychology Workshop, (World Scientific) Progress in Neural Processing, vol. 17, pp. 139-149, 2007. Web page.
  35. P.C.R. Lane and F. Gobet, ‘Applying multi-criteria optimisation to develop cognitive models’, in Proceedings of the Fifth UK Workshop on Computational Intelligence, pp. 28-35, 2005.
  36. P.C.R. Lane and F. Gobet, ‘Discovering predictive variables when evolving cognitive models’, in S.Singh, M.Singh, C.Apte and P.Perner (eds.), Proceedings of the Third International Conference on Advances in Pattern Recognition (Berlin: Springer Verlag), LNCS 3686, pp. 108-117, 2005.
  37. P.C.R. Lane and F. Gobet, ‘Multi-task learning and transfer: The effect of algorithm representation’, in Meta-Learning Workshop of the Twenty-Second International Conference on Machine Learning, 2005.
  38. F. Gobet and P.C.R. Lane, ‘A distributed framework for semi-automatically developing architectures of brain and mind’, in Proceedings of the First International Conference on e-Social Science, 2005.
  39. P.C.R. Lane, A. K. Sykes, and F. Gobet, ‘Combining low-level perception with expectations in CHREST’, in F. Schmalhofer, R. M. Young and G. Katz (eds.), Proceedings of EuroCogSci’03, (Mahwah, NJ: Lawrence Erlbaum Associates) pp. 205-210, 2003.
  40. P.C.R. Lane, P.C-H. Cheng and F. Gobet, ‘Learning perceptual chunks for problem decomposition’, in Proceedings of the Twenty-Third Annual Conference of the Cognitive Science Society, pp. 528-33, 2001. Proceedings.
  41. P.C.R. Lane, F. Gobet and P.C-H. Cheng, ‘Learning-based constraints on schemata’, in Proceedings of the Twenty-Second Annual Conference of the Cognitive Science Society, pp. 776-81, 2000. Proceedings.
  42. P.C.R. Lane, P.C-H. Cheng and F. Gobet, ‘Learning perceptual schemas to avoid the utility problem’, in M. Bramer, A. Macintosh, and F. Coenen (Eds.) Research and Development in Intelligent Systems XVI: Proceedings of ES99, the Nineteenth SGES International Conference on Knowledge-Based Systems and Artificial Intelligence, (Springer-Verlag) pp. 72-82, 1999.
  43. P.C.R. Lane and J.B. Henderson, ‘Simple Synchrony Networks: Learning to parse natural language with Temporal Synchrony Variable Binding’, in Proceedings of the 1998 International Conference on Artificial Neural Networks, pp. 615-20, 1998.
  44. P.C.R. Lane, ‘Simple Synchrony Networks: Learning generalisations across syntactic constituents’, in Proceedings of the Thirteenth European Conference on Artificial Intelligence, pp. 469-70, 1998.
  45. J.B. Henderson and P.C.R. Lane, ‘A connectionist architecture for learning to parse’, in Proceedings of the Seventeenth International Conference on Computational Linguistics and the Thirty-Sixth Annual Meeting of the Association for Computational Linguistics, 1998.

Book Chapters and Encyclopedia Entries

  1. F. Gobet, M. Lloyd-Kelly and P.C.R.Lane, ‘Computational models of expertise’, in Hambrick, D.Z., Campitelli, G., and Macnamara, B.N. (Eds.), The science of expertise, (New York: Psychology Press), pp.347-364, 2017. Web page.
  2. P.D. Sozou, P.C.R. Lane, M. Addis and F. Gobet, ‘Computational scientific discovery’, in Magnani, L. and Bertolotti, T. (Eds.), Springer Handbook of Model-Based Science, (New York, NY: Springer), pp.719-734, 2017.
  3. F. Gobet and P.C.R. Lane, ‘Human problem solving: Beyond Newell et al.’s (1958) Elements of a theory of human problem solving’, in D. Groome and M.W. Eysenck (Eds.), Cognitive Psychology: Revisiting the Classic Studies, Thousand Oaks, CA: Sage, pp.133-45, 2015.
  4. F. Gobet and P.C.R. Lane, ‘Bounded rationality and learning’, in N.M. Seel (Ed.) Encyclopedia of the Sciences of Learning, New York, NY: Springer, pp.482-484, 2012.
  5. F. Gobet and P.C.R. Lane, ‘Chunking mechanisms and learning’, in N.M. Seel (Ed.) Encyclopedia of the Sciences of Learning, New York, NY: Springer, pp.541-544, 2012.
  6. F. Gobet and P.C.R. Lane, ‘Learning in the CHREST cognitive architecture’, in N.M. Seel (Ed.) Encyclopedia of the Sciences of Learning, New York, NY: Springer, pp.1920-1922, 2012.
  7. P.C.R. Lane, ‘Order effects in neural networks (Order out of chaos)’, in F.E. Ritter, J. Nerb, T. O’Shea and E. Lehtinen (Eds.), In order to learn: How ordering effects in machine learning illuminate human learning and vice versa. New York, NY: Oxford University Press, 2007. Web page.
  8. F. Gobet and P.C.R. Lane, ‘How do order effects arise in a cognitive model?’, in F.E. Ritter, J. Nerb, T. O’Shea and E. Lehtinen (Eds.), In order to learn: How ordering effects in machine learning illuminate human learning and vice versa. New York, NY: Oxford University Press, 2007. Web page.
  9. F. Gobet and P.C.R. Lane, ‘The CHREST architecture of cognition: Listening to empirical data’, in D.N.Davis (Ed.), Visions of Mind: Architectures for Cognition and Affect, Information Science Publishing, 2005. Web page.
  10. P.C.R. Lane and F. Gobet, ‘Learning and recognition: Capturing an expert’s perceptual knowledge’, in C. Faucher, L. Jain, and N. Ichalkaranje (Eds.), Innovations in Knowledge Engineering, 2003.

Unrefereed Conference Papers and Abstracts

  1. M. Lloyd-Kelly, F. Gobet and P.C.R. Lane, ‘Be-Bop-A-Lula: A CHREST Model of Infant Word Segmentation’, poster presented at the Fifth Implicit Learning Seminar, 23rd-25th June, 2016.
  2. P.D. Sozou, P.C.R. Lane, F. Gobet and M. Addis, ‘Automatic generation of scientific theories to fit experimental data’, poster presented at The 2014 International Conference of the Royal Statistical Society, 1st-4th September, 2014.
  3. M. Addis, F. Gobet, P.C.R. Lane and P.D. Sozou, ‘Computational scientific discovery and cognitive science theories’, presented at Cognitive Science of Science: Kazimierz Naturalist Workshop, 22nd-24th August, 2014.
  4. M. Addis, F. Gobet, P.C.R. Lane and P.D. Sozou, ‘Computational scientific discovery and cognitive science theories’, presented at IACAP 14: Conference of the International Association for Computing and Philosophy, 2nd-4th July, 2014.
  5. P.C.R. Lane, P.D. Sozou, F. Gobet and M. Addis, ‘Analysing psychological data by evolving computational models’ presented at European Conference on Data Analysis, 2nd-4th July, 2014.
  6. F. Gobet, P.C.R. Lane, P.D. Sozou and M. Addis, ‘Automatic generation of scientific theories in psychology’, poster presented at the 26th Annual Convention of the Association for Psychological Science (APA), 2014.
  7. F. Gobet, M. Addis, P.C.R. Lane and P.D. Sozou, ‘Automatically generating scientific theories about decision making under uncertainty’, in Workshop ‘Forecasting, monitoring, controlling: Dealing with a dynamic world’, at University College London, 19th-20th September, 2013.
  8. P.C.R. Lane and F. Gobet, ‘Building models of learning and expertise with CHREST’, in Proceedings of the Thirty-Second Annual Meeting of the Cognitive Science Society, 2010.
  9. A.A.Albrecht, P.C.R. Lane, K. Steinhöfel, ‘On the number of local maxima in MAX-SAT instances’, in Book of Abstracts: London Algorithms Workshop (LAW), p. 2, London, 2009.
  10. A.W. Rainer, P.C.R. Lane and J.A. Malcolm, ‘A fast copy detection tool for forensic analysis of suspect documents’, in Proceedings of the Third International Conference on Cybercrime Forensics Education & Training, 2009.
  11. P.C.R. Lane and F. Gobet, ‘EPAM/CHREST Tutorial: Fifty years of simulating human learning’, in Proceedings of the Ninth International Conference on Cognitive Modelling, 2009.
  12. P.C.R. Lane and F. Gobet, ‘EPAM/CHREST Tutorial: Fifty years of simulating human learning’, in N.A. Taatgen and J. van Rijn (Eds.) Proceedings of the Thirty-First Annual Conference of the Cognitive Science Society, pp. 13-14, (Austin, TX: Cognitive Science Society) 2009. Website.
  13. P.C.R. Lane and J.A. Malcolm, ‘Searching for plagiarism: An evaluation of WebFerret’, in University of Hertfordshire Annual Learning and Teaching Conference, 2008.
  14. P.C.R. Lane, J.A. Malcolm and A.W. Rainer, ‘WebFerret: Plagiarism detection across the web’, in FEIS Learning & Teaching Conference, 2007.
  15. P.C.R. Lane, C. M. Lyon and J. A. Malcolm, ‘Demonstration of the Ferret Plagiarism Detector’, in Proceedings of the Second International Plagiarism Conference, 2006.
  16. P.C.R. Lane and F. Gobet, ‘CHREST Tutorial: Simulations of human learning’, in Proceedings of the Twenty-Seventh Annual Meeting of the Cognitive Science Society, p. 17, 2005. Web page.
  17. F. Gobet and P.C.R. Lane, ‘CHREST tutorial: Simulations of human learning’, in Proceedings of the Twenty-Sixth Annual Meeting of the Cognitive Science Society, p. 3, 2004. Web page.
  18. P.C.R. Lane, F. Gobet and P.C-H. Cheng, ‘Learning perceptual chunks in a computational model of problem solving with diagrams’, in Proceedings of the Third International Conference on Cognitive Modelling, pp. 285-86, 2000.
  19. P.C.R. Lane, P.C-H. Cheng, and F. Gobet, ‘Problem solving with diagrams: Modelling the learning of perceptual information’, in Proceedings of the Twenty-First Annual Meeting of the Cognitive Science Society, 1999.

Reviews and Commentaries

  1. F. Gobet, M. Lloyd-Kelly and P.C.R. Lane, ‘What’s in a name? The multiple meanings of “chunk” and “chunking”’, Frontiers in Psychology, 7(102), 2016. Web page.
  2. F. Gobet, P.C.R. Lane and M. Lloyd-Kelly, ‘Chunks, schemata and retrieval structures: Past and current computational models’, Frontiers in Psychology, 6(1785), 2015. Web page.
  3. P.C.R. Lane and F. Gobet, ‘Towards a model of expectation-driven perception’, AISB Quarterly, 114:7, 2003.
  4. P.C.R. Lane, ‘Review of van Hemmel et al. (Eds.), Models of neural networks IV: Early vision and attention’, Expert Update, 5:57-8, 2002.
  5. P.C.R. Lane, ‘Review of S. Raudys, Statistical and neural classifiers: An integrated approach to design’, Expert Update, 4:37-38, 2001.
  6. P.C.R. Lane and F. Gobet, ‘Simple environments fail as illustrations of intelligence: A review of R. Pfeifer and C. Scheier, Understanding Intelligence, Cambridge: MIT Press, 1999’, Artificial Intelligence, 127:261-67, 2001. (Refereed book review.)
  7. P.C.R. Lane, P.C-H. Cheng, and F. Gobet, ‘The CHREST model of active perception and its role in problem solving’, Behavioral and Brain Sciences, (commentary on B. Hommel et al., ‘Theory of Event Coding’), 24:892-3, 2001.
  8. P.C.R. Lane, F. Gobet and P.C-H. Cheng, ‘What forms a chunk? Lessons from the CHREST computational model of expertise’, Behavioral and Brain Sciences, (commentary on N. Cowan, ‘The magical number 4 in short-term memory’), 4:128-128, 2001.

Technical and Project Reports

  1. P.C.R.Lane, ‘A guide to GEM programming in C using AHCC,’ 2017. Web page.
  2. P.D. Green, P.C.R. Lane, A.W. Rainer and S. Scholz, ‘Analysing Ferret XML reports to estimate the density of copied code’, Technical Report 501, Science and Technology Research Institute, University of Hertfordshire, 2010. Download.
  3. P.D. Green, P.C.R. Lane, A.W. Rainer and S. Scholz, ‘Unscrambling code clones for one-to-one matching of duplicated code’, Technical Report 502, Science and Technology Research Institute, University of Hertfordshire, 2010. Download.
  4. P.D. Green, P.C.R. Lane, A.W. Rainer and S. Scholz, ‘An introduction to slice-based cohesion and coupling metrics’, Technical Report 488, Science and Technology Research Institute, University of Hertfordshire, 2009. Download.
  5. J.P. Bao, C.M. Lyon, P.C.R. Lane, W. Ji, and J.A. Malcolm, ‘Comparing different text similarity methods’, Technical Report 461, Science and Technology Research Institute, University of Hertfordshire, 2007. Download.
  6. J.P. Bao, C.M. Lyon, P.C.R. Lane, W. Ji, and J.A. Malcolm, ‘Copy detection in Chinese documents using the Ferret: A report on experiments’, Technical Report 456, Science and Technology Research Institute, University of Hertfordshire, 2006. Download.
  7. P.C.R. Lane, F. Gobet, and P.C-H. Cheng, ‘Predicting perceptual chunks with a computational model of problem solving with diagrams’, ESRC CREDIT Technical Report No. 67, University of Nottingham, 2000.
  8. P.C.R. Lane, ‘Simple Synchrony Networks: A new connectionist architecture applied to natural language parsing’, Ph.D. Thesis, Dept. of Computer Science, University of Exeter, England, 2000. Download.
  9. P.C.R. Lane, P.C-H. Cheng, and F. Gobet, ‘Problem solving with diagrams: Modelling the learning of perceptual information’, ESRC CREDIT Technical Report No. 59, University of Nottingham, 1999.
  10. P.C.R. Lane, ‘Machine learning and pattern recognition’, M.Sc. Thesis, Dept. of Computer Science, University of Exeter, England, 1995.
  11. P.C.R. Lane, ‘An implementation of ARTMAP’, Project Report, Dept. of Computer Science, University of Exeter, England, 1995. Download.

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