Please send notice of any missing publications or corrections to andrew@aomartin.co.uk, please include where possible a BibTeX entry and a PDF of the publication.
A. Ravi, M. Giriprasad, and P. Naganjaneyulu. Sar images denoising using a novel stochastic diffusion wavelet scheme. Cluster Computing, pages 1--9, 2017. [ bib | .pdf ]
J. M. Bishop, S. J. Nasuto, T. Tanay, E. B. Roesch, and M. C. Spencer. Hex and the single anthill: playing games with aunt hillary. In Fundamental Issues of Artificial Intelligence, pages 367--388. Springer, 2016. [ bib | .pdf ]
M. A. Javaheri Javid, W. Alghamdi, R. Zimmer, and M. M. al-Rifaie. A comparative analysis of detecting symmetries in toroidal topology. In Intelligent Systems and Applications, pages 323--344. Springer, 2016. [ bib | .pdf ]
H. A. Alhakbani and M. M. al-Rifaie. Exploring feature-level duplications on imbalanced data using stochastic diffusion search. In Multi-Agent Systems and Agreement Technologies, pages 305--313. Springer, 2016. [ bib | DOI | http | .pdf ]
M. M. al-Rifaie and J. M. Bishop. Weak and strong computational creativity. In Computational creativity research: Towards creative machines, pages 37--49. Springer, 2015. [ bib | .pdf ]
M. M. al-Rifaie and J. M. Bishop. Swarmic paintings and colour attention. In P. Machado, J. McDermott, and A. Carballal, editors, Evolutionary and Biologically Inspired Music, Sound, Art and Design, volume 7834 of Lecture Notes in Computer Science, pages 97--108. Springer Berlin Heidelberg, 2013. [ bib | DOI | http | .pdf ]
M. M. al-Rifaie and J. M. Bishop. Swarmic sketches and attention mechanism. In P. Machado, J. McDermott, and A. Carballal, editors, Evolutionary and Biologically Inspired Music, Sound, Art and Design, volume 7834 of Lecture Notes in Computer Science, pages 85--96. Springer Berlin Heidelberg, 2013. [ bib | DOI | http | .pdf ]
M. G. Omran and A. Salman. Probabilistic stochastic diffusion search. In Swarm Intelligence, pages 300--307. Springer, 2012. [ bib | http | .pdf ]
M. M. al-Rifaie, A. Aber, J. M. Bishop, et al. Cooperation of nature and physiologically inspired mechanism in visualisation. In Biologically-Inspired Computing for the Arts: Scientific Data through Graphics, pages 31--58. IGI Global, 2012. [ bib | .pdf ]
D. Coulter and E. Ehlers. Cellular automata and immunity amplified stochastic diffusion search. In Advances in Practical Multi-Agent Systems, pages 21--32. Springer, 2011. [ bib | .pdf ]
M. M. al-Rifaie, J. M. Bishop, and T. Blackwell. Resource allocation and dispensation impact of stochastic diffusion search on differential evolution algorithm. In Nature Inspired Cooperative Strategies for Optimization (NICSO 2011), pages 21--40. Springer, 2011. [ bib | .pdf ]
S. Nasuto and J. M. Bishop. Stabilizing swarm intelligence search via positive feedback resource allocation. In Nature Inspired Cooperative Strategies for Optimization (NICSO 2007), pages 115--123. Springer, 2008. [ bib | .pdf ]
D. R. Myatt, S. Nasuto, and J. M. Bishop. Alternative recruitment strategies for Stochastic Diffusion Search. In L. M. Rocha, L. S. Yaeger, M. A. Bedau, D. Floreano, R. L. Goldstone, and A. Vespignani, editors, Artificial Life X, volume 10. MIT Press, Cambridge, MA, May 2006. [ bib ]
K. De Meyer, S. J. Nasuto, and J. M. Bishop. Stochastic diffusion search: Partial function evaluation in swarm intelligence dynamic optimisation. In Stigmergic Optimization, pages 185--207. Springer, 2006. [ bib | .pdf ]
J. M. Bishop, S. J. Nasuto, and K. De Meyer. Dynamic knowledge representation in connectionist systems. In Artificial Neural Networks-ICANN 2002, pages 308--313. Springer, 2002. [ bib | .pdf ]
K. De Meyer, J. M. Bishop, and S. J. Nasuto. Small-world effects in lattice stochastic diffusion search. In Artificial Neural Networks-ICANN 2002, pages 147--152. Springer, 2002. [ bib | .pdf ]
S. J. Nasuto, K. Dautenhahn, and J. M. Bishop. Communication as an emergent metaphor for neuronal operation. In Computation for metaphors, analogy, and agents, pages 365--379. Springer, 1999. [ bib | .doc | .pdf ]
S. J. Nasuto, K. Dautenhahn, and J. M. Bishop. Communication as an emergent metaphor for neuronal operation. In C. Nehaniv, editor, Plenary Working Papers in Computation for Metaphors, Analogy and Agents. Aizu, Japan, pages 65--70. Springer, 1998. [ bib ]
J. M. Bishop and P. Torr. The stochastic search network. In Neural networks for vision, speech and natural language, pages 370--387. Springer, 1992. [ bib | .doc | .pdf ]
H. Alhakbani and M. M. al-Rifaie. Feature selection using Stochastic Diffusion Search. In Proceedings of the Genetic and Evolutionary Computation Conference, pages 385--392. ACM, 2017. [ bib | .pdf ]
H. A. Alhakbani and M. M. al-Rifaie. A swarm intelligence approach in undersampling majority class. In International Conference on Swarm Intelligence, pages 225--232. Springer, 2016. [ bib | DOI | http | .pdf ]
J. M. Bishop, A. O. Martin, and E. J. Robinson. Local termination criteria for Stochastic Diffusion Search: a comparison with the behaviour of ant nest-site selection. In International Conference on Computational Collective Intelligence, pages 474--486. Springer, 2016. [ bib | .pdf ]
M. M. al-Rifaie, F. Leymarie, W. Latham, and J. M. Bishop. Swarmic autopoiesis: Decoding de kooning. In Proc. AISB 2016: 3rd Symposium on Computational Creativity, Sheffield, UK, 2016. [ bib | .pdf ]
F. M. al-Rifaie and M. M. al-Rifaie. Maximising overlap score in dna sequence assembly problem by Stochastic Diffusion Search. In Intelligent Systems and Applications, pages 301--321. Springer, 2016. [ bib | .pdf ]
H. Sajedi and M. Azizi. Satellite broadcast scheduling by boosted differential evolution. In Computational Intelligence and Informatics (CINTI), 2016 IEEE 17th International Symposium on, pages 000175--000180. IEEE, 2016. [ bib | .pdf ]
M. M. al-Rifaie, M. Yee-King, and M. d'Inverno. Investigating swarm intelligence for performance prediction. In EDM, pages 264--269, 2016. [ bib | .pdf ]
M. M. al-Rifaie, D. Joyce, S. Shergill, and J. M. Bishop. Investigating Stochastic Diffusion Search in data clustering. In SAI Intelligent Systems Conference (IntelliSys), 2015, pages 187--194. IEEE, 2015. [ bib | .pdf ]
A. M. al-Rifaie and M. M. al-Rifaie. Generative music with Stochastic Diffusion Search. In International Conference on Evolutionary and Biologically Inspired Music and Art, pages 1--14. Springer, 2015. [ bib | .pdf ]
F. M. al-Rifaie and M. M. al-Rifaie. Investigating Stochastic Diffusion Search in DNA sequence assembly problem. In SAI Intelligent Systems Conference (IntelliSys), 2015, pages 625--631. IEEE, 2015. [ bib | .pdf ]
V. Bhasin, P. Bedi, and A. Singhal. Feature selection for steganalysis based on modified Stochastic Diffusion Search using fisher score. In Advances in Computing, Communications and Informatics (ICACCI, 2014 International Conference on), pages 2323--2330. IEEE, 2014. [ bib | .pdf ]
P. Bedi, V. Bhasin, N. Mittal, and T. Chatterjee. FS-SDS: Feature selection for JPEG steganalysis using Stochastic Diffusion Search. In Systems, Man and Cybernetics (SMC), 2014 IEEE International Conference on, pages 3797--3802. IEEE, 2014. [ bib | .pdf ]
M. A. Javaheri Javid, M. M. al-Rifaie, and R. Zimmer. Detecting symmetry in cellular automata generated patterns using swarm intelligence. In International Conference on Theory and Practice of Natural Computing, pages 83--94. Springer, 2014. [ bib | .pdf ]
M. M. al-Rifaie and J. M. Bishop. Swarm intelligence and weak artificial creativity. In AAAI Spring Symposium: Creativity and (Early) Cognitive Development, 2013. [ bib | .pdf ]
T. Tanay, J. M. Bishop, S. Nasuto, E. Roesch, and M. Spencer. Stochastic Diffusion Search applied to trees: a swarm intelligence heuristic performing monte-carlo tree search. In AISB 2013 Proceedings, University of Exeter, UK, 2013. [ bib | .pdf ]
M. Evans, C. J. Osborne, and J. Ferryman. Multicamera object detection and tracking with object size estimation. In Advanced Video and Signal Based Surveillance (AVSS), 2013 10th IEEE International Conference on, pages 177--182. IEEE, 2013. [ bib | .pdf ]
M. M. al-Rifaie and A. Aber. Identifying metastasis in bone scans with Stochastic Diffusion Search. In Information Technology in Medicine and Education (ITME), 2012 International Symposium on, volume 1, pages 519--523. IEEE, 2012. [ bib | http | .pdf ]
M. M. Al-Rifaie, A. Aber, and A. M. Oudah. Utilising Stochastic Diffusion Search to identify metastasis in bone scans and microcalcifications on mammographs. In Bioinformatics and Biomedicine Workshops (BIBMW), 2012 IEEE International Conference on, pages 280--287. IEEE, 2012. [ bib | .pdf ]
L. Sheng-wei and Z. Jin. Cellular SDS algorithm for the rectilinear steiner minimum tree. In Digital Manufacturing and Automation (ICDMA), 2012 Third International Conference on, pages 272--276. IEEE, 2012. [ bib | .pdf ]
M. M. al-Rifaie, A. Aber, and J. M. Bishop. Swarms search for cancerous lesions: Artificial intelligence use for accurate identification of bone metastasis on bone scans. In The European Federation of National Associations of Orthopaedics and Traumatology (EFORT), 13th EFORT Congress, Berlin, Germany, 2012. [ bib | .pdf ]
M. M. al-Rifaie and J. M. Bishop. Weak versus strong computational creativity. In J. M. Bishop and Y. J. Erden, editors, The 5th AISB Symposium on Computing and Philosophy: Computing, Philosophy and the Question of Bio- Machine Hybrids, pages 64--67, Birmingham, UK, 2012. Proc. AISB/IACAP World Congress in honour of Alan Turing. [ bib | .pdf ]
L. S. Marcolino and H. Matsubara. Multi-agent monte carlo go. In The 10th International Conference on Autonomous Agents and Multiagent Systems, volume 1, pages 21--28. International Foundation for Autonomous Agents and Multiagent Systems, 2011. [ bib | .pdf ]
M. M. al-Rifaie, J. M. Bishop, and T. Blackwell. An investigation into the merger of Stochastic Diffusion Search and particle swarm optimisation. In Proceedings of the 13th annual conference on Genetic and evolutionary computation, pages 37--44. ACM, 2011. [ bib | .pdf ]
M. G. H. Omran, I. Moukadem, S. al Sharhan, and M. Kinawi. Stochastic Diffusion Search for continuous global optimization. In ICSI 2011: International conference on swarm intelligence, 2011. [ bib | .pdf ]
N. Salamanos, S. Lopatatzidis, M. Vazirgiannis, and A. Thomas. Advertising network formation based on Stochastic Diffusion Search and market equilibria. In Proceedings of the 28th ACM International Conference on Design of Communication, pages 81--87. ACM, 2010. [ bib | .pdf ]
R. J. Cant and C. S. Langensiepen. Methods for automated object placement in virtual scenes. In Computer Modelling and Simulation, 2009. UKSIM'09. 11th International Conference on, pages 431--436. IEEE, 2009. [ bib | .pdf ]
J. Govil, J. Govil, and A. Nandra. An insight into swarm intelligence for adapting to business and technology. In Region 5 Conference, 2008 IEEE, pages 1--5. IEEE, 2008. [ bib | .pdf ]
I. Moser and T. Hendtlass. A simple and efficient multi-component algorithm for solving dynamic function optimisation problems. In Evolutionary Computation, 2007. CEC 2007. IEEE Congress on, pages 252--259. IEEE, 2007. [ bib | .pdf ]
S. J. Nasuto, J. M. Bishop, and K. De Meyer. NESTER: a spiking neuron connectionist implementation of stochastic diffusion search. In International Conference on Brain Inspired Cognitive Systems (BICS '06), Lesbos, Greece, 2006. [ bib | .pdf ]
D. R. Myatt, S. J. Nasuto, and J. M. Bishop. Exploration and exploitation in stochastic diffusion search. In Exploration vs Exploitation in Naturally Inspired Search, Symposium on Nature Inspired Systems. AISB, 4 2006. [ bib | .pdf ]
K. De Meyer, J. M. Bishop, and S. J. Nasuto. Stochastic diffusion: using recruitment for search. Evolvability and interaction: evolutionary substrates of communication, signalling, and perception in the dynamics of social complexity (ed. P. McOwan, K. Dautenhahn & CL Nehaniv) Technical Report, 393:60--65, 2003. [ bib | .pdf ]
S. Hurley and R. M. Whitaker. An agent based approach to site selection for wireless networks. In Proceedings of the 2002 ACM symposium on Applied computing, pages 574--577. ACM, 2002. [ bib | .pdf ]
J. M. Bishop and S. Nasuto. Communicating neurons - an alternative connectionism. Proc. WNNW99, York, 1999. [ bib | .doc | .pdf ]
S. J. Nasuto, J. M. Bishop, S. Lauria, et al. Time complexity analysis of the Stochastic Diffusion Search. In NC, pages 260--266, 1998. [ bib | .doc | .pdf ]
P. Beattie and J. M. Bishop. Localization of the senario wheelchair. In Proceedings of MobiNet Symposium Mobile Robotics Technology for Health Care Services, pages 287--293, 1997. [ bib ]
H. Grech-Cini and G. T. McKee. Locating the mouth region in images of human faces. In Optical Tools for Manufacturing and Advanced Automation, pages 458--465. International Society for Optics and Photonics, 1993. [ bib | .pdf ]
J. M. Bishop and R. Mitchell. Optimisation of tuple size in a hybrid stochastic search. In Proc. WnnW '93, pages 139--145, 1993. [ bib | .pdf ]
J. M. Bishop. A hybrid network for feature extraction. In INNC 90 Paris: International Neural Network Conference, July 9-13, 1990, Palais des Congres, Paris, France, Volume 2, page 50, 1990. [ bib | .pdf ]
J. M. Bishop. Stochastic searching networks. In Proc. 1st IEE Conf. on Artifical neural networks, pages 329--331, 1989. [ bib | .pdf ]
M. Ramanan and P. Vivekanandan. Efficient data integrity and data replication in cloud using stochastic diffusion method. Cluster Computing, March 2018. [ bib | DOI | http | .pdf ]
S. Ragunthar, T.and Selvakumar. A wrapper based feature selection in bone marrow plasma cell gene expression data. Cluster Computing, February 2018. [ bib | DOI | http | .pdf ]
M. A. Javaheri Javid, W. Alghamdi, A. Ursyn, R. Zimmer, and M. M. al-Rifaie. Swarmic approach for symmetry detection of cellular automata behaviour. Soft Computing, pages 1--15, August 2017. [ bib | DOI | http | .pdf ]
M. M. al-Rifaie, F. Fol Leymarie, W. Latham, and J. M. Bishop. Swarmic autopoiesis and computational creativity. Connection Science, pages 1--19, 2017. [ bib | .pdf ]
J. M. Bishop and M. M. al-Rifaie. Autopoiesis, creativity and dance. Connection science, 29(1):21--35, 2017. [ bib | .pdf ]
V. Chandrasekar, S. S. Kumar, and T. Maheswari. Authentication based on keystroke dynamics using stochastic diffusion algorithm. Stochastic Analysis and Applications, 34(1):155--164, 2016. [ bib | DOI | arXiv | http | .pdf ]
J. Sheeba and S. P. Devaneyan. Recommendation of keywords using swarm intelligence techniques. In Proceedings of the International Conference on Informatics and Analytics, page 8. ACM, 2016. [ bib | .pdf ]
A. Shanthi and M. Karthikeyan. Improving gabor filter bank design and svm optimization using cuckoo search for mild cognitive impairment classification. Journal of Medical Imaging and Health Informatics, 6(3):784--787, 2016. [ bib | .pdf ]
M. M. al-Rifaie, A. Cropley, D. Cropley, and J. M. Bishop. On evil and computational creativity. Connection Science, 28(2):171--193, 2016. [ bib | .pdf ]
A. A. Salman, I. Ahmad, and M. G. Omran. Stochastic diffusion binary differential evolution to solve multidimensional knapsack problem. International Journal of Machine Learning and Computing, 6(2):130, 2016. [ bib | .pdf ]
A. A. Salman, I. Ahmad, and M. G. Omran. A metaheuristic algorithm to solve satellite broadcast scheduling problem. Information Sciences, 322:72--91, 2015. [ bib | .pdf ]
M. M. al-Rifaie, A. Aber, and D. J. Hemanth. Deploying swarm intelligence in medical imaging identifying metastasis, micro-calcifications and brain image segmentation. IET systems biology, 9(6):234--244, 2015. [ bib | .pdf ]
S. J. Nasuto and J. M. Bishop. Steady state resource allocation analysis of the stochastic diffusion search. Biologically Inspired Cognitive Architectures, 12:65--76, 2015. [ bib | .pdf ]
H. Williams and J. M. Bishop. Stochastic Diffusion Search: A comparison of swarm intelligence parameter estimation algorithms with ransac. Algorithms, 7(2):206--228, 2014. [ bib | .pdf ]
I. M. El-Henawy and M. M. Ismail. A hybrid swarm intelligence technique for solving integer multi-objective problems. International Journal of Computer Applications, 87(3), 2014. [ bib | .pdf ]
M. M. al-Rifaie and J. M. Bishop. Stochastic Diffusion Search review. Paladyn, Journal of Behavioral Robotics, 4(3):155--173, 2013. [ bib | .pdf ]
E. B. Roesch, M. Spencer, S. J. Nasuto, T. Tanay, and J. M. Bishop. Exploration of the functional properties of interaction: computer models and pointers for theory. Constructivist Foundations, 9(1):26--33, 2013. [ bib | .pdf ]
J. Zhang, M. Dong, and F. F. Chen. A bottleneck steiner tree based multi-objective location model and intelligent optimization of emergency logistics systems. Robotics and Computer-Integrated Manufacturing, 29(3):48--55, 2013. [ bib | .pdf ]
M. M. al-Rifaie, J. M. Bishop, and T. Blackwell. Information sharing impact of Stochastic Diffusion Search on differential evolution algorithm. Memetic Computing, 4(4):327--338, 2012. [ bib | .html | .pdf ]
M. M. al-Rifaie, J. M. Bishop, and S. Caines. Creativity and autonomy in swarm intelligence systems. Cognitive Computation, 4(3):320--331, 2012. [ bib | .html | .pdf ]
M. M. al-Rifaie, J. M. Bishop, A. Aber, et al. Creative or not? birds and ants draw with muscles. Proceedings of AISB'11 Computing and Philosophy, pages 23--30, 2011. [ bib | .pdf ]
M. M. al-Rifaie, J. M. Bishop, and T. M. Blackwell. An investigation into the use of swarm intelligence for an evolutionary algorithm optimisation; the optimisation performance of differential evolution algorithm coupled with Stochastic Diffusion Search. International Conference on Evolutionary Computation Theory and Application (ECTA 2011), 3:1--6, 2011. [ bib | http | .pdf ]
L. Yong and M. Liang. Stochastic Diffusion Search algorithm for quadratic knapsack problem. Control Theory & Applications, 8:014, 2011. [ bib | .pdf ]
J. Zhang, Y.-l. Zhao, and L. Ma. Solving the euclidean steiner minimum tree using cellular Stochastic Diffusion Search algorithm. Journal of Shanghai Jiaotong University (Science), 16(6):734--741, 2011. [ bib | .pdf ]
S. J. Nasuto, J. M. Bishop, and K. De Meyer. Communicating neurons: A connectionist spiking neuron implementation of Stochastic Diffusion Search. Neurocomputing, 72(4):704--712, 2009. [ bib | .pdf ]
D. Teodorović. Swarm intelligence systems for transportation engineering: Principles and applications. Transportation Research Part C: Emerging Technologies, 16(6):651--667, 2008. [ bib | .pdf ]
M. Evans, J. Ferryman, et al. Group stochastic search for object detection and tracking. Advanced Video and Signal Based Surveillance, 2005. AVSS 2005. IEEE Conference on, 2005. [ bib | .pdf ]
D. R. Myatt, J. M. Bishop, and S. J. Nasuto. Minimum stable convergence criteria for Stochastic Diffusion Search. Electronics Letters, 40(2):112--113, 2004. [ bib | .pdf ]
S. J. Nasuto and J. M. Bishop. Steady state resource allocation analysis of the Stochastic Diffusion Search. arXiv preprint cs/0202007, 2002. [ bib | .pdf ]
K. De Meyer, J. M. Bishop, and S. J. Nasuto. Attention through self-synchronisation in the spiking neuron Stochastic Diffusion Network. Consc. and Cogn, 9(2):81--81, 2000. [ bib | .pdf ]
T. Morey, K. De Meyer, S. J. Nasuto, and J. M. Bishop. Implementation of the spiking neuron Stochastic Diffusion Network on parallel hardware. Consciousness and Cognition, 2000. [ bib | .pdf ]
S. Nasuto and J. M. Bishop. Convergence analysis of Stochastic Diffusion Search. PARALLEL ALGORITHMS AND APPLICATION, 14(2):89--107, 1999. [ bib | .doc | .pdf ]
P. Beattie and J. M. Bishop. Self-localisation in the 'SENARIO' autonomous wheelchair. Journal of Intelligent and Robotic Systems, 22(3-4):255--267, 1998. [ bib | .doc | .pdf ]
N. I. Katevas, N. M. Sgouros, S. G. Tzafestas, G. Papakonstantinou, P. Beattie, J. M. Bishop, P. Tsanakas, and D. Koutsouris. The autonomous mobile robot senario: a sensor aided intelligent navigation system for powered wheelchairs. Robotics & Automation Magazine, IEEE, 4(4):60--70, 1997. [ bib | .pdf ]
H. Williams. Stochastic diffusion search processes. Master's thesis, Goldsmiths, University of London, London, United Kingdom, 2010. Cognitive Computing MSc. [ bib | .pdf ]
Q. Nguyen and J. M. Bishop. Exploration of data driven sds vs. coupled sds. Master's thesis, Goldsmiths, University of London, London, United Kingdom, 2008. Cognitive Computing MSc. [ bib | .pdf ]
R. Summers. Stochastic diffusion search a basis for a model of visual attention? Master's thesis, Keele University, Keele, Newcastle ST5 5BG, 1998. [ bib | .pdf ]
M. M. al-Rifaie et al. Information sharing impact of stochastic diffusion search on population-based algorithms. PhD thesis, Goldsmiths, University of London, 2011. [ bib | .pdf ]
A. Nircan. Stochastic diffusion search and voting methods. PhD thesis, Bogaziki University, 2006. [ bib ]
D. R. Myatt. Analysis of stochastic diffusion search and its application to robust estimation. PhD thesis, University of Reading, 2005. [ bib | .pdf ]
K. De Meyer. Foundations of stochastic diffusion search. PhD thesis, University of Reading, 2004. [ bib | .pdf ]
P. Beattie. The design and implementation of a Focused Stochastic Diffusion Network to solve the self-localisation problem on an autonomous wheelchair. PhD thesis, University of Reading, 2000. [ bib | .pdf ]
S. Nasuto. Resource allocation analysis of the stochastic diffusion search. PhD thesis, University of Reading, 1999. [ bib | .pdf ]
H. Grech-Cini. Locating facial features. PhD thesis, University of Reading, 1995. [ bib ]
J. M. Bishop. Anarchic techniques for pattern classification. PhD thesis, University of Reading, 1989. [ bib | .pdf ]
T. Tanay. Game-tree exploration using Stochastic Diffusion Search. Technical report, Goldsmiths, University of London, 2012. [ bib | .pdf ]
T. Oguri and Y. Kotani. Move decision method based on SDS. Technical report, 14th Game Programming Workshop, Computer Shogi Association, 2009. [ bib | .pdf ]
D. R. Myatt. Robust estimation in high noise and highly dimensional data sets with applications to machine vision, 2002. [ bib | .pdf ]
K. De Meyer. Explorations in Stochastic Diffusion Search: Soft-and hardware implementations of biologically inspired spiking neuron Stochastic Diffusion networks. Technical report, Technical Report KDM/JMB/2000, 2000. [ bib | .pdf ]
T. Morey. Parallel implementation of a spiking neuron Stochastic Diffusion network. Technical report, Cybernetics Dept., Reading University, 1999. [ bib | .pdf ]
T. Dent. Do pharaoh's ants (monomorium pharaohis) forage using the Stochastic Diffusion algorithm? Technical report, Cybernetics Dept., Reading University, 1999. [ bib | .pdf ]
S. Nasuto. Analysis of Stochastic Diffusion Search. Technical report, Technical Report Nr. SJN/JMB/1996-1, University of Reading, UK., 1996. [ bib ]
J. M. Bishop. NESTOR: A spiking neuron implementation of sds, 2017. [ bib | .pdf ]
M. M. al-Rifaie. Swarmic sketches with swarmic attention, 2013. 17th International Conference Information Visualisation (iV2013, London, UK) and 10th International Conference Computer Graphics, Imaging and Visualization (cgiv2013, Macau, China). [ bib | .png ]
M. M. al-Rifaie. Ants intelligence framework; identifying traces of cancer, 2013. In The House of Commons, UK Parliment. SET for BRITAIN 2013. Poster exhibitions in Biological and Biomedical Science. [ bib | .png | www: | .pdf ]
R. Hughes. Stochastic Diffusion Search with reinforcement learning. In Proc. School Conference for Annual Research Projects (SCARP), Reading, UK, 2012. [ bib | .pdf ]
M. M. al-Rifaie. Swarming robots and possible medical applications, 2011. In: International Society for the Electronic Arts (ISEA 2011), Istanbul, Turkey. [ bib | http | .pdf ]
M. M. al-Rifaie. When birds and ants set off to draw, 2011. 15th International Conference Information Visualisation (iV2011, London) and 8th International Conference Computer Graphics, Imaging and Visualization (cgiv2011, Singapore). [ bib | .pdf ]
M. M. al-Rifaie. Sds and bone scintigraphy. YouTube, 7 2011. [ bib | http ]
M. M. al-Rifaie, J. M. Bishop, et al. The mining game: a brief introduction to the Stochastic Diffusion Search metaheuristic. Q: The magazine of AISB, 130:8--9, 2010. [ bib | .pdf ]
A. Hernandez-Carrascal and S. J. Nasuto. A swarm intelligence method for feature tracking in AMV derivation. In Ninth International Winds Workshop, 2008. [ bib | http | .pdf ]
D. R. Myatt and J. M. Bishop. Data driven Stochastic Diffusion Search for robust estimation, 2003. [ bib | .pdf ]
D. R. Myatt and J. M. Bishop. Data driven stochastic diffusion networks for robust high-dimensionality manifold estimation-more fun than you can shake a hyperplane at. In Proc. School Conference for Annual Research Projects (SCARP), Reading, UK, 2003. [ bib | .pdf ]
J. M. Bishop. Coupled stochastic diffusion processes. In Proc. School Conference for Annual Research Projects (SCARP), Reading, UK, pages 185--187, 2003. [ bib | .doc | .pdf ]
D. B. Driver. Stochastic Diffusion Search for simple terrain recognition. In Proc. School Conference for Annual Research Projects (SCARP), Reading, UK, 2003. [ bib | .pdf ]
I. Clegg. SDS for pose recovery and tracking of 3D models. In Proc. School Conference for Annual Research Projects (SCARP), Reading, UK, 2003. [ bib | .pdf ]
R. Clephan. Robot search via SDS. In Proc. School Conference for Annual Research Projects (SCARP), Reading, UK, 2003. [ bib | .pdf ]
T. Dearden. Robot search via Stochastic Diffusion Search. In Proc. School Conference for Annual Research Projects (SCARP), Reading, UK, 2003. [ bib | .pdf ]
M. Oakley. Extracting feature data from bifurcating trees using Stochastic Diffusion Search. In Proc. School Conference for Annual Research Projects (SCARP), Reading, UK, 2003. [ bib | .pdf ]
J. M. Bishop, K. de Meyer, and S. Nasuto. Recruiting robots perform Stochastic Diffusion Search. In Proc. School Conference for Annual Research Projects (SCARP), Reading, UK, 2002. [ bib ]
D. Jones. Constrained Stochastic Diffusion Search. In SCARP 2002, 2002. [ bib | .pdf ]
D. R. Myatt and J. M. Bishop. Applying the principles of Stochastic Diffusion Search to invariant object recognition. In SCARP 2001, pages 35--38, 2001. [ bib ]
N. Nicolaou and J. M. Bishop. Speech recognition using Stochastic Diffusion Search. In SCARP 2001, pages 15--20, 2001. [ bib ]
M. Warriner. Hardware Stochastic Diffusion Search. Technical report, Dept. Cybernetics, University of Reading, UK, 2000. [ bib | .pdf ]
S. J. Nasuto and J. M. Bishop. Multiple drafts or global workspace? In Neural Correlates of Consciousness: Empirical and Conceptual Questions, page 56, 1998. [ bib | .pdf ]
S. J. Nasuto and J. M. Bishop. Neural Stochastic Diffusion Search network-a theoretical solution to the binding problem. In Proc. ASSC2, Bremen, volume 19, 1998. [ bib | .html | .pdf ]
J. M. Bishop. Stochastic diffusion search. Scholarpedia. Accessed: 27 July 2017. [ bib ]
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