Now showing items 1-20 of 36

  • 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 ...
  • BPGA-EDA for the multi-mode resource constrained project scheduling problem. 

    Ayodele, Mayowa; McCall, John; Regnier-Coudert, Olivier (IEEE https://doi.org/10.1109/CEC.2016.7744222, 2016-11-21)
    AYODELE, M., MCCALL, J. and REGNIER-COUDERT, O. 2016. BPGA-EDA for the multi-mode resource constrained project scheduling problem. In the Proceedings of the IEEE congress on evolutionary computation (CEC), 24-29 July 2016, Vancouver, Canada. Piscataway, NJ: IEEE [online], pages 3417-3424. Available from: https://doi.org/10.1109/CEC.2016.7744222
    The Multi-mode Resource Constrained Project Scheduling Problem (MRCPSP) has been of research interest for over two decades. The problem is composed of two interacting sub problems: mode assignment and activity scheduling. ...
  • 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. ...
  • Estimation of distribution algorithms for the multi-mode resource constrained project scheduling problem. 

    Ayodele, Mayowa; McCall, John; Regnier-Coudert, Olivier (IEEE, 2017-06-05)
    AYODELE, M., MCCALL, J. and REGNIER-COUDERT, O. 2017. Estimation of distribution algorithms for the multi-mode resource constrained project scheduling problem. To be presented at the IEEE congress on evolutionary computation 2017, 5-8 June 2017, San Sebastian, Spain.
    Multi-Mode Resource Constrained Project Problem (MRCPSP) is a multi-component problem which combines two interacting sub-problems; activity scheduling and mode assignment. Multi-component problems have been of research ...
  • 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 ...
  • Generating easy and hard problems using the Proximate Optimality Principle. [Dataset] 

    McCall, John; Christie, Lee A.; Brownlee, Alexander Edward Ian (OpenAIR@RGU, 2015-07-11)
    MCCALL, J.A.W., CHRISTIE, L.A. and BROWNLEE, A.E.I. 2015. Generating easy and hard problems using the Proximate Optimality Principle. [Dataset]. Held on OpenAIR [online]. Available from: https://hdl.handle.net/10059/1407
    These data were gathered to investigate the hypothesis that coherent functions will be easy and anti-coherent functions will be hard for a hillclimber. We generated 10 coherent functions for each length on bit-strings 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. ...