Agent-Based Problem Solving: The Ant Colonies Metaphor

Stefan Wagner; Michael Affenzeller; Ismail Khalil Ibrahim

Agent-Based Problem Solving: The Ant Colonies Metaphor

Stefan Wagner, Michael Affenzeller, Ismail Khalil Ibrahim

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

Abstract

In this paper the analogy between biological swarms and artificial multiagent systems is pointed out. As an example the steps required to model the artificial optimization technique called Ant Colony Optimization starting from the foraging behaviour of natural ant colonies are explained in detail. During the development of the model the authors use the language of multiagent systems to highlight the suitability of such an approach.

Original language	English
Title of host publication	The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003)
Publisher	Österreichische Computer Gesellschaft (OCG)
Pages	317-323
ISBN (Print)	3-85403-170-10
Publication status	Published - 2003
Event	The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003) - Jakarta, Indonesia Duration: 15 Sept 2003 → 17 Sept 2003 http://www.tk.uni-linz.ac.at/iiwas/

Conference

Conference	The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003)
Country/Territory	Indonesia
City	Jakarta
Period	15.09.2003 → 17.09.2003
Internet address	http://www.tk.uni-linz.ac.at/iiwas/

Keywords

Heuristic Optimization
Swarm Intelligence
Ant Colony Optimization
Ant Systems

Cite this

@inproceedings{e6ca6c215a8b4afda816df585bfd96f7,

title = "Agent-Based Problem Solving: The Ant Colonies Metaphor",

abstract = "In this paper the analogy between biological swarms and artificial multiagent systems is pointed out. As an example the steps required to model the artificial optimization technique called Ant Colony Optimization starting from the foraging behaviour of natural ant colonies are explained in detail. During the development of the model the authors use the language of multiagent systems to highlight the suitability of such an approach.",

keywords = "Heuristic Optimization, Swarm Intelligence, Ant Colony Optimization, Ant Systems, Heuristic Optimization, Swarm Intelligence, Ant Colony Optimization, Ant Systems",

author = "Stefan Wagner and Michael Affenzeller and {Khalil Ibrahim}, Ismail",

year = "2003",

language = "English",

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booktitle = "The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003)",

publisher = "{\"O}sterreichische Computer Gesellschaft (OCG)",

note = "The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003) ; Conference date: 15-09-2003 Through 17-09-2003",

url = "http://www.tk.uni-linz.ac.at/iiwas/",

}

Wagner, S , Affenzeller, M & Khalil Ibrahim, I 2003, Agent-Based Problem Solving: The Ant Colonies Metaphor. in The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003). Österreichische Computer Gesellschaft (OCG), pp. 317-323, The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003), Jakarta, Indonesia, 15.09.2003.

Agent-Based Problem Solving: The Ant Colonies Metaphor. / Wagner, Stefan ; Affenzeller, Michael; Khalil Ibrahim, Ismail.
The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003). Österreichische Computer Gesellschaft (OCG), 2003. p. 317-323.

Research output: Chapter in Book/Report/Conference proceedings › Conference contribution › peer-review

TY - GEN

T1 - Agent-Based Problem Solving: The Ant Colonies Metaphor

AU - Wagner, Stefan

AU - Affenzeller, Michael

AU - Khalil Ibrahim, Ismail

PY - 2003

Y1 - 2003

N2 - In this paper the analogy between biological swarms and artificial multiagent systems is pointed out. As an example the steps required to model the artificial optimization technique called Ant Colony Optimization starting from the foraging behaviour of natural ant colonies are explained in detail. During the development of the model the authors use the language of multiagent systems to highlight the suitability of such an approach.

AB - In this paper the analogy between biological swarms and artificial multiagent systems is pointed out. As an example the steps required to model the artificial optimization technique called Ant Colony Optimization starting from the foraging behaviour of natural ant colonies are explained in detail. During the development of the model the authors use the language of multiagent systems to highlight the suitability of such an approach.

KW - Heuristic Optimization

KW - Swarm Intelligence

KW - Ant Colony Optimization

KW - Ant Systems

KW - Heuristic Optimization

KW - Swarm Intelligence

KW - Ant Colony Optimization

KW - Ant Systems

UR - http://www.heuristiclab.com/publications/papers/wagner03a.pdf

UR - https://www.researchgate.net/profile/Michael_Affenzeller2/publication/221238023_Agent-based_Problem_Solving_The_Ant_Colonies_Metaphor/links/00b49525e3b48a44b4000000/Agent-based-Problem-Solving-The-Ant-Colonies-Metaphor.pdf

M3 - Conference contribution

SN - 3-85403-170-10

SP - 317

EP - 323

BT - The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003)

PB - Österreichische Computer Gesellschaft (OCG)

T2 - The Fifth International Conference on Information Integration and Web-based Applications & Services (iiWAS 2003)

Y2 - 15 September 2003 through 17 September 2003

ER -

Agent-Based Problem Solving: The Ant Colonies Metaphor

Abstract

Conference

Keywords

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