A Multiple Pheromone Ant Clustering Algorithm

被引：3

作者：

Chircop, Jan ^{[1
]}

Buckingham, Christopher D. ^{[1
]}

机构：

[1] Aston Univ, Birmingham B4 7ET, W Midlands, England

来源：

NATURE INSPIRED COOPERATIVE STRATEGIES FOR OPTIMIZATION (NICSO 2013) | 2014年 / 512卷

关键词：

Ant Colony Algorithms; Swarm Intelligence; Emergent Behaviour; Cluster Analysis; Classification; COLONY OPTIMIZATION;

D O I：

10.1007/978-3-319-01692-4_2

中图分类号：

TP18 [人工智能理论];

学科分类号：

081104 ; 0812 ; 0835 ; 1405 ;

摘要：

Ant colony optimisation algorithms model the way ants use pheromones for marking paths to important locations in their environment. Pheromone traces are picked up, followed, and reinforced by other ants but also evaporate over time. Optimal paths attract more pheromone and less useful paths fade away. The main innovation of the proposed Multiple Pheromone Ant Clustering Algorithm (MPACA) is to mark objects using many pheromones, one for each value of each attribute describing the objects in multidimensional space. Every object has one or more ants assigned to each attribute value and the ants then try to find other objects with matching values, depositing pheromone traces that link them. Encounters between ants are used to determine when ants should combine their features to look for conjunctions and whether they should belong to the same colony. This paper explains the algorithm and explores its potential effectiveness for cluster analysis.

引用

页码：13 / 27

页数：15

共 40 条

[11]

Deneubourg J., 1990, Proceedings of the First International Conference of Simulation of Adaptive Behavior on from Animals to Animats, P356

[12] Ant colony optimization -: Artificial ants as a computational intelligence technique [J].

Dorigo, Marco ;

Birattari, Mauro ;

Stuetzle, Thomas .

IEEE COMPUTATIONAL INTELLIGENCE MAGAZINE, 2006, 1 (04) :28-39

[13] The role of multiple pheromones in food recruitment by ants [J].

Dussutour, A. ;

Nicolis, S. C. ;

Shephard, G. ;

Beekman, M. ;

Sumpter, D. J. T. .

JOURNAL OF EXPERIMENTAL BIOLOGY, 2009, 212 (15) :2337-2348

[14] An Adaptive Ant-Based Clustering Algorithm with Improved Environment Perception [J].

El-Feghi, I. ;

Errateeb, M. ;

Ahmadi, M. ;

Sid-Ahmed, M. A. .

2009 IEEE INTERNATIONAL CONFERENCE ON SYSTEMS, MAN AND CYBERNETICS (SMC 2009), VOLS 1-9, 2009, :1431-+

[15] The linear separability problem: Some testing methods [J].

Elizondo, D .

IEEE TRANSACTIONS ON NEURAL NETWORKS, 2006, 17 (02) :330-344

[16]

Ester M., 1996, KDD-96 Proceedings. Second International Conference on Knowledge Discovery and Data Mining, P226

[17] The challenge of biomimetic design for carbon-neutral buildings using termite engineering [J].

French, John R. J. ;

Ahmed , Berhan M. .

INSECT SCIENCE, 2010, 17 (02) :154-162

[18] The dynamics of herds: From individuals to aggregations [J].

Gueron, S ;

Levin, SA ;

Rubenstein, DI .

JOURNAL OF THEORETICAL BIOLOGY, 1996, 182 (01) :85-98

[19]

Guntsch Michael., 2004, ANT ALGORITHMS STOCH

[20]

Hall M., 2009, SIGKDD Explorations, V11, P10, DOI DOI 10.1145/1656274.1656278

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