Now showing items 1-20 of 29

  • Adaptive dynamic control of quadrupedal robotic gaits with Artificial Reaction Networks. 

    Gerrard, Claire E.; McCall, John; Coghill, George M.; Macleod, Christopher (Springer http://dx.doi.org/10.1007/978-3-642-34475-6_34, 2012-11)
    GERRARD, C.E., MCCALL, J., COGHILL, G. M. and MACLEOD, C., 2012. Adaptive dynamic control of quadrupedal robotic gaits with Artificial Reaction Networks. In: T. HUANG, Z. ZENG, C. LI and C. S. LEUNG, eds. Neural Information Processing: 19th International Conference, ICONIP 2012, Doha, Qatar, November 12-15, 2012, Proceedings, Part 1. Berlin: Springer, pp. 280-287.
    The Artificial Reaction Network (ARN) is a bio-inspired connectionist paradigm based on the emerging field of Cellular Intelligence. It has properties in common with both AI and Systems Biology techniques including Artificial ...
  • Adaptive heterogeneous parallelism for semi-empirical lattice dynamics in computational materials science. 

    Garba, Michael (Robert Gordon University School of Computing Science and Digital Media, 2015-04)
    With the variability in performance of the multitude of parallel environments available today, the conceptual overhead created by the need to anticipate runtime information to make design-time decisions has become ...
  • An application of genetic algorithms to chemotherapy treatment. 

    Petrovski, Andrei (Robert Gordon University School of Computing Science & Digital Media, 1998-12)
    The present work investigates methods for optimising cancer chemotherapy within the bounds of clinical acceptability and making this optimisation easily accessible to oncologists. Clinical oncologists wish to be able to ...
  • Applications and design of cooperative multi-agent ARN-based systems. 

    Gerrard, Claire E.; McCall, John; Macleod, Christopher; Coghill, George M. (Springer. http://dx.doi.org/10.1007/s00500-014-1330-9, 2015-06)
    GERRARD, C. E., MCCALL, J., MACLEOD, C. and COGHILL, G. M., 2015. Applications and design of cooperative multi-agent ARN-based systems. Soft Computing, 19 (6), pp. 1581-1594.
    The Artificial Reaction Network (ARN) is an Artificial Chemistry inspired by Cell Signalling Networks (CSNs). Its purpose is to represent chemical circuitry and to explore the computational properties responsible for ...
  • Approximating true relevance model in relevance feedback. 

    Zhang, Peng (Robert Gordon University School of Computing Science and Digital Media, 2013-01)
    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. ...
  • Artificial chemistry approach to exploring search spaces using Artificial Reaction Network agents. 

    Gerrard, Claire E.; McCall, John; Macleod, Christopher; Coghill, George M. (IEEE http://dx.doi.org/10.1109/CEC.2013.6557702, 2013)
    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: IEEE Congress on Evolutionary Computation (CEC) 2013 : Proceedings. 20 – 23 June 2013. IEEE. pp. 1201-1208.
    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 ...
  • Artificial Reaction Networks. 

    Gerrard, Claire E.; McCall, John; Coghill, George M.; Macleod, Christopher (2011-09-20)
    In this paper we present a novel method of simulating cellular intelligence, the Artificial Reaction Network (ARN). The ARN can be described as a modular S-System, with some properties in common with other Systems Biology ...
  • Autonomic behavioural framework for structural parallelism over heterogeneous multi-core systems. 

    Goli, Mehdi (Robert Gordon University School of Computing Science and Digital Media, 2015-05)
    With the continuous advancement in hardware technologies, significant research has been devoted to design and develop high-level parallel programming models that allow programmers to exploit the latest developments in ...
  • Bayesian network structure learning using characteristic properties of permutation representations with applications to prostate cancer treatment. 

    Regnier-Coudert, Olivier (Robert Gordon University School of Computing Science and Digital Media, 2013-05)
    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 ...
  • Combining biochemical network motifs within an ARN-agent control system. 

    Gerrard, Claire E.; McCall, John; Macleod, Christopher; Coghill, George M. (IEEE http://dx.doi.org/10.1109/UKCI.2013.6651281, 2013-09)
    GERRARD, C. E., MCCALL, J., MACLEOD, C. and COGHILL, G. M., 2013. Combining biochemical network motifs within an ARN-agent control system. In: Y. JIN and S. A. THOMAS, eds. Proceedings of the 13th UK Workshop on Computational Intelligence (UKCI) 2013 9-11 September 2013. New York: IEEE. pp. 8-15.
    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 ...
  • Computational aspects of cellular intelligence and their role in artificial intelligence. 

    Gerrard, Claire E. (Robert Gordon University School of Computing Science and Digital Media, 2014-07)
    The work presented in this thesis is concerned with an exploration of the computational aspects of the primitive intelligence associated with single-celled organisms. The main aim is to explore this “Cellular Intelligence” ...
  • DEUM: A Framework for an Estimation of Distribution Algorithm based on Markov Random Fields 

    Shakya, Siddhartha (The Robert Gordon University School of Computing, Faculty of Design and Technology, The Robert Gordon University, Aberdeen, UK, 2006-04)
    Estimation of Distribution Algorithms (EDAs) belong to the class of population based optimisation algorithms. They are motivated by the idea of discovering and exploiting the interaction between variables in the solution. ...
  • Experimental user interface design toolkit for interaction research (IDTR). 

    Golovine, Jean Claude Raymond Rolin (Robert Gordon University School of Computing Science and Digital Media., 2013-05)
    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 ...
  • Exploring aspects of cell intelligence with artificial reaction networks. 

    Gerrard, Claire E.; McCall, John; Coghill, George M.; Macleod, Christopher (Springer. http://dx.doi.org/10.1007/s00500-013-1174-8, 2014-10)
    GERRARD, C. E., MCCALL, J., COGHILL, G. M. and MACLEOD, C., 2014. Exploring aspects of cell intelligence with artificial reaction networks. Soft Computing, 18 (10), pp. 1899-1912.
    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 ...
  • Generating easy and hard problems using the Proximate Optimality Principle. 

    McCall, John; Christie, Lee A.; Brownlee, Alexander Edward Ian (ACM http://doi.acm.org/10.1145/2739482.2764890, 2015)
    MCCALL, J. A. W., CHRISTIE, L. A. and BROWNLEE, A. E. I, 2015. Generating easy and hard problems using the Proximate Optimality Principle. In: Proceedings of the Companion Publication of the 2015 Annual Conference on Genetic and Evolutionary Computation (GECCO Companion '15). New York: ACM. pp. 767-768.
    We present an approach to generating problems of variable difficulty based on the well-known Proximate Optimality Principle (POP), often paraphrased as "similar solutions have similar fitness". We explore definitions of ...
  • Incorporating a metropolis method in a distribution estimation using Markov random field algorithm. 

    Shakya, Siddhartha; McCall, John; Brown, Deryck (IEEE http://dx.doi.org/10.1109/CEC.2005.1555017, 2005-09)
    SHAKYA, S., MCCALL, J. and BROWN, D., 2005. Incorporating a metropolis method in a distribution estimation using Markov random field algorithm. In: Proceedings of the IEEE Congress on Evolutionary Computation (CEC 2005), Volume 3. 2-5 September 2005. New York: IEEE. pp. 2576-2583.
    Markov Random Field (MRF) modelling techniques have been recently proposed as a novel approach to probabilistic modelling for Estimation of Distribution Algorithms (EDAs)[34, 4]. An EDA using this technique, presented ...
  • An inductive logic programming approach to learning which uORFs regulate gene expression. 

    Selpi (The Robert Gordon University School of Computing, 2008-03)
    Some upstream open reading frames (uORFs) regulate gene expression (i.e. they are functional) and can play key roles in keeping organisms healthy. However, how uORFs are involved in gene regulation is not het fully understood. ...
  • Minimal walsh structure and ordinal linkage of monotonicity-invariant function classes on bit strings. 

    Christie, Lee A.; McCall, John; Lonie, David P. (ACM http://dx.doi.org/10.1145/2576768.2598240, 2014)
    CHRISTIE, L. A., MCCALL, J. A. W. and LONIE, D. P., 2014. Minimal walsh structure and ordinal linkage of monotonicity-invariant function classes on bit strings. In: Proceedings of the 2014 Annual Conference on Genetic and Evolutionary Computation (GECCO '14). 12-16 July 2014. New York: ACM. pp. 333-340.
    Problem structure, or linkage, refers to the interaction between variables in a black-box fitness function. Discovering structure is a feature of a range of algorithms, including estimation of distribution algorithms (EDAs) ...
  • Multi-objective optimisation of cancer chemotherapy using evolutionary algorithms. 

    Petrovski, Andrei; McCall, John (Springer http://dx.doi.org/10.1007/3-540-44719-9, 2001)
    PETROVSKI, A. and MCCALL, J., 2001. Multi-objective optimisation of cancer chemotherapy using evolutionary algorithms. In: ZITZLEF, E., DEB, K., THIELE, L., COELLO, C. and CORNE, D. Evolutionary Multi-criterion Optimization : First International Conference, EMO 2001, Zurich, Switzerland, March 2001 : Proceedings. Berlin: Springer. pp. 531-545.
    The main objectives of cancer treatment in general, and of cancer chemotherapy in particular, are to eradicate the tumour and to prolong the patient survival time. Traditionally, treatments are optimised with only ...
  • Multi-objective particle swarm optimisation: methods and applications. 

    Al Moubayed, Noura (Robert Gordon University School of Computing Science and Digital Media, 2014-02)
    Solving real life optimisation problems is a challenging engineering venture. Since the early days of research on optimisation it was realised that many problems do not simply have one optimisation objective. This led to ...