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George Macleod Coghill
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- affiliation: University of Aberdeen, UK
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2020 – today
- 2023
- [j30]AbuBakr Awad
, Wei Pang
A survey on physarum polycephalum intelligent foraging behaviour and bio-inspired applications. Artif. Intell. Rev. 56(1): 1-26 (2023) - [j29]AbuBakr Awad
A novel Physarum-inspired competition algorithm for discrete multi-objective optimisation problems. Soft Comput. 27(20): 14699-14719 (2023) - 2022
- [c38]Adinath Ghadage, Dewei Yi
Multi-stage Bias Mitigation for Individual Fairness in Algorithmic Decisions. ANNPR 2022: 40-52 - [c37]Debinal Rajan, Shouyong Jiang, Dewei Yi
Enhanced Affinity Propagation Clustering on Heterogeneous Information Network. UKCI 2022: 334-346 - 2021
- [c36]Luc Frachon, Wei Pang
An Immune-Inspired Approach to Macro-Level Neural Ensemble Search. CEC 2021: 2491-2498 - [c35]James Forrest, Somayajulu Sripada, Wei Pang, George M. Coghill:
Are Contrastive Explanations Useful? SICSA XAI 2021: 9-16 - [i4]Yingfang Yuan, Wenjun Wang, George M. Coghill, Wei Pang:
A Novel Genetic Algorithm with Hierarchical Evaluation Strategy for Hyperparameter Optimisation of Graph Neural Networks. CoRR abs/2101.09300 (2021) - [i3]AbuBakr Awad, Wei Pang, David Lusseau, George M. Coghill:
A Survey on Physarum Polycephalum Intelligent Foraging Behaviour and Bio-Inspired Applications. CoRR abs/2103.00172 (2021) - 2020
- [j28]Yan Wang
An Efficient v-Minimum Absolute Deviation Distribution Regression Machine. IEEE Access 8: 85533-85551 (2020) - [j27]Muhammad Usman
Inferring structure and parameters of dynamic system models simultaneously using swarm intelligence approaches. Memetic Comput. 12(3): 267-282 (2020)
2010 – 2019
- 2019
- [c34]Muhammad Usman, AbuBakr Awad
Inferring structure and parameters of dynamic systems using particle swarm optimization. GECCO (Companion) 2019: 101-102 - [c33]AbuBakr Awad
A physarum-inspired competition algorithm for solving discrete multi-objective optimization problems. GECCO (Companion) 2019: 195-196 - [c32]AbuBakr Awad, Wei Pang
A Hexagonal Cell Automaton Model to Imitate Physarum Polycephalum Competitive Behaviour. ALIFE 2019: 203-210 - [c31]Hadeel Albalawi, Wei Pang
Swarm Inspired Approaches for K-prototypes Clustering. UKCI 2019: 201-209 - [i2]Luc Frachon, Wei Pang
ImmuNeCS: Neural Committee Search by an Artificial Immune System. CoRR abs/1911.07729 (2019) - 2018
- [c30]James Forrest, Somayajulu Sripada, Wei Pang, George M. Coghill:
Towards making NLG a voice for interpretable Machine Learning. INLG 2018: 177-182 - [c29]Ge Ou, Yan Wang, Lan Huang, Wei Pang
ε-Distance Weighted Support Vector Regression. PAKDD (1) 2018: 209-220 - [c28]Anthony Chapman, Wei Pang
CLEMI-Imputation Evaluation. SACI 2018: 373-378 - [c27]Kuratu M. Tanimu, Wei Pang, George M. Coghill:
A Conceptual Framework of Starlings Swarm Intelligence Intrusion Prevention for Software Defined Networks. SICSA ReaLX 2018 - [c26]AbuBakr Awad
Physarum Inspired Connectivity and Restoration for Wireless Sensor and Actor Networks. UKCI 2018: 327-338 - 2017
- [c25]Ge Ou, Yan Wang, Wei Pang
Large margin distribution machine recursive feature elimination. ICSAI 2017: 1518-1523 - 2016
- [c24]Nura Mukhtar, George Macleod Coghill
FdDCA: A Novel Fuzzy Deterministic Dendritic Cell Algorithm. GECCO (Companion) 2016: 1007-1010 - 2015
- [j26]Wei Pang
QML-AiNet: An immune network approach to learning qualitative differential equation models. Appl. Soft Comput. 27: 148-157 (2015) - [j25]Wei Pang
Qualitative, semi-quantitative, and quantitative simulation of the osmoregulation system in yeast. Biosyst. 131: 40-50 (2015) - [j24]Zujian Wu, Wei Pang
An Integrated Qualitative and Quantitative Biochemical Model Learning Framework Using Evolutionary Strategy and Simulated Annealing. Cogn. Comput. 7(6): 637-651 (2015) - [j23]Claire E. Gerrard, John A. W. McCall
Applications and design of cooperative multi-agent ARN-based systems. Soft Comput. 19(6): 1581-1594 (2015) - [j22]Zujian Wu, Wei Pang
An integrative top-down and bottom-up qualitative model construction framework for exploration of biochemical systems. Soft Comput. 19(6): 1595-1610 (2015) - [c23]Chukwuemeka David Emele, Vitalij Spakov, Wei Pang, Jone Bone, George M. Coghill:
ADOVA: Anomaly Detection in Online and Virtual spAces. COOS@AAMAS 2015: 38-41 - 2014
- [j21]Wei Pang
QML-Morven: A novel framework for learning qualitative differential equation models using both symbolic and evolutionary approaches. J. Comput. Sci. 5(5): 795-808 (2014) - [j20]Claire E. Gerrard, John A. W. McCall
Exploring aspects of cell intelligence with artificial reaction networks. Soft Comput. 18(10): 1899-1912 (2014) - [c22]Wei Pang
An immune network approach to learning qualitative models of biological pathways. IEEE Congress on Evolutionary Computation 2014: 1030-1037 - [c21]Wei Pang
Fuzzy qualitative simulation with multivariate constraints. FUZZ-IEEE 2014: 575-582 - 2013
- [j19]Anna V. Kononova
Advances in computational intelligence (UKCI 2012). Soft Comput. 17(12): 2181-2183 (2013) - [c20]Claire Gerrard, John A. W. McCall
Artificial chemistry approach to exploring search spaces using Artificial Reaction Network agents. IEEE Congress on Evolutionary Computation 2013: 1201-1208 - [c19]Claire E. Gerrard, John A. W. McCall, George M. Coghill, Christopher MacLeod:
Artificial Reaction Network Agents. ECAL 2013: 957-964 - [c18]Claire Gerrard, John A. W. McCall
Combining biochemical network motifs within an ARN-agent control system. UKCI 2013: 8-15 - [c17]Zujian Wu, Wei Pang
Stepwise modelling of biochemical pathways based on qualitative model learning. UKCI 2013: 31-37 - 2012
- [c16]Claire Gerrard, John A. W. McCall
Temporal Patterns in Artificial Reaction Networks. ICANN (1) 2012: 1-8 - [c15]Claire Gerrard, John A. W. McCall
Adaptive Dynamic Control of Quadrupedal Robotic Gaits with Artificial Reaction Networks. ICONIP (1) 2012: 280-287 - [c14]Donald Matheson, George M. Coghill
Integrating natural language generation and model-based reasoning for explanation generation. UKCI 2012: 1-7 - [c13]Wei Pang
Extended kernel subset analysis for qualitative model learning. UKCI 2012: 1-7 - 2011
- [j18]Tao You, Ian Stansfield
Analysing GCN4 translational control in yeast by stochastic chemical kinetics modelling and simulation. BMC Syst. Biol. 5: 131 (2011) - [j17]Chee Seng Chan
Recent Advances in Fuzzy Qualitative Reasoning. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(3): 417-422 (2011) - [j16]George Macleod Coghill
Fuzzy Qualitative Reasoning about Dynamic Systems Containing Trigonometric Relationships. Int. J. Uncertain. Fuzziness Knowl. Based Syst. 19(3): 477-498 (2011) - [j15]Wei Pang
An immune-inspired approach to qualitative system identification of biological pathways. Nat. Comput. 10(1): 189-207 (2011) - [i1]George Macleod Coghill, Ross D. King, Ashwin Srinivasan:
Qualitative System Identification from Imperfect Data. CoRR abs/1111.0051 (2011) - 2010
- [j14]Wei Pang
Learning Qualitative Differential Equation models: a survey of algorithms and applications. Knowl. Eng. Rev. 25(1): 69-107 (2010) - [c12]Wei Pang
Learning Qualitative Metabolic Models Using Evolutionary Methods. FCST 2010: 436-441 - [c11]Wei Pang
QML-AiNet: An Immune-Inspired Network Approach to Qualitative Model Learning. ICARIS 2010: 223-236
2000 – 2009
- 2009
- [j13]George Macleod Coghill
Incremental state based diagnosis. Adv. Eng. Informatics 23(3): 309-322 (2009) - [j12]Honghai Liu
Fuzzy qualitative trigonometry. Int. J. Approx. Reason. 51(1): 71-88 (2009) - [c10]Wei Pang
An Immune-Inspired Approach to Qualitative System Identification of the Detoxification Pathway of Methylglyoxal. ICARIS 2009: 151-164 - 2008
- [j11]George Macleod Coghill
Qualitative System Identification from Imperfect Data. J. Artif. Intell. Res. 32: 825-877 (2008) - [j10]Honghai Liu
Fuzzy Qualitative Robot Kinematics. IEEE Trans. Fuzzy Syst. 16(3): 808-822 (2008) - 2007
- [j9]Tao You, Alistair J. P. Brown, George M. Coghill:
A quantitative model for the GCN4 translational control in Saccharomyces cerevisiae. BMC Syst. Biol. 1(S-1): P1 (2007) - [j8]Honghai Liu, George Macleod Coghill
Qualitative kinematics of planar robots: Intelligent connection. Int. J. Approx. Reason. 46(3): 525-541 (2007) - [c9]George Macleod Coghill:
Fuzzy Qualitative Behaviour Prioritisation. FUZZ-IEEE 2007: 1-6 - [c8]Mehdi Khoury, Frank Guerin, George Macleod Coghill:
Learning dynamic models of compartment systems by combining symbolic regression with fuzzy vector envisionment. GECCO (Companion) 2007: 2769-2776 - [c7]Wei Pang
Modified clonal selection algorithm for learning qualitative compartmental models of metabolic systems. GECCO (Companion) 2007: 2887-2894 - [c6]Honghai Liu, David J. Brown, George Macleod Coghill
Geometrical Representation of Quantity Space and Its Application to Robot Motion Description. KES (2) 2007: 18-25 - [p1]Simon M. Garrett, George Macleod Coghill, Ashwin Srinivasan, Ross D. King:
Learning Qualitative Models of Physical and Biological Systems. Computational Discovery of Scientific Knowledge 2007: 248-272 - 2006
- [j7]Chris J. Price, Louise Travé-Massuyès, Robert Milne, Liliana Ironi
Qualitative futures. Knowl. Eng. Rev. 21(4): 317-334 (2006) - [c5]George M. Coghill, Guofu Wu:
Incremental Fault Isolation for Dynamic Processes. SGAI Conf. 2006: 333-345 - 2005
- [j6]Ross D. King
On the use of qualitative reasoning to simulate and identify metabolic pathway. Bioinform. 21(9): 2017-2026 (2005) - [j5]Honghai Liu, George Macleod Coghill
A model-based approach to robot fault diagnosis. Knowl. Based Syst. 18(4-5): 225-233 (2005) - [c4]Honghai Liu, George Macleod Coghill:
Fuzzy Qualitative Trigonometry. SMC 2005: 1291-1296 - 2004
- [j4]George M. Coghill
Towards Model-based Methods for Developing Model-based Systems. Int. J. Gen. Syst. 33(5): 485-504 (2004) - [c3]George Macleod Coghill, Simon M. Garrett, Ross D. King:
Learning Qualitative Metabolic Models. ECAI 2004: 445-449 - [c2]Honghai Liu, George Macleod Coghill:
Qualitative Modelling of Planar Robots. ECAI 2004: 1051-1052 - [c1]Honghai Liu, George M. Coghill:
A Model-Based Approach to Robot Fault Diagnosis. SGAI Conf. (Applications) 2004: 137-150 - 2001
- [j3]George Macleod Coghill, Qiang Shen:
On the specification of multiple models for diagnosis of dynamic systems. AI Commun. 14(2): 93-104 (2001)
1990 – 1999
- 1998
- [j2]Mike J. Chantler, George Macleod Coghill, Qiang Shen, Roy Leitch:
Selecting tools and techniques for model-based diagnosis. Artif. Intell. Eng. 12(1-2): 81-98 (1998) - 1996
- [b1]George Macleod Coghill:
Mycroft : a framework for constraint based fuzzy qualitative reasoning. Heriot-Watt University, Edinburgh, UK, 1996 - 1994
- [j1]Roy Leitch, Mike J. Chantler
A Preliminary Specification Methodology for Model-based Diagnosis. Ann. Math. Artif. Intell. 11(1-4): 11-32 (1994)
Coauthor Index
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