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Of robot ants and elephants

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Gal A. KaminkaAuthors Info & Claims

AAMAS '09: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1

Pages 81 - 88

Published: 10 May 2009 Publication History

Abstract

Investigations of multi-robot systems often make implicit assumptions concerning the computational capabilities of the robots. Despite the lack of explicit attention to the computational capabilities of robots, two computational classes of robots emerge as focal points of recent research: Robot Ants and robot Elephants. Ants have poor memory and communication capabilities, but are able to communicate using pheromones, in effect turning their work area into a shared memory. By comparison, elephants are computationally stronger, have large memory, and are equipped with strong sensing and communication capabilities. Unfortunately, not much is known about the relation between the capabilities of these models in terms of the tasks they can address. In this paper, we present formal models of both ants and elephants, and investigate if one dominates the other. We present two algorithms: AntEater, which allows elephant robots to execute ant algorithms; and ElephantGun, which converts elephant algorithms---specified as Turing machines---into ant algorithms. By exploring the computational capabilities of these algorithms, we reach interesting conclusions regarding the computational power of both models.

References

[1]

E. Şahin. Swarm robotics: From sources of inspiration to domains of application. In Swarm Robotics: SAB 2004 International Workshop, volume 3342 of Lecture Notes in Computer Science, pages 10--20. Springer, 2005.

Digital Library

[2]

N. Hazon, F. Mieli, and G. A. Kaminka. Towards robust on-line multi-robot coverage. In ICRA, 2006.

[3]

S. Koenig and Y. Liu. Terrain coverage with ant robots: a simulation study. In AGENTS, pages 600--607, New York, NY, USA, 2001. ACM.

Digital Library

[4]

S. Koenig, B. Szymanski, and Y. Liu. Efficient and inefficient ant coverage methods. Annals of Mathematics and Artificial Intelligence, 31(1--4):41--76, 2001.

Digital Library

[5]

T. H. Labella, M. Dorigo, and J.-L. Deneubourg. Division of labor in a group of robots inspired by ants' foraging behavior. ACM Transactions on Autonomous Adaptive Systems, 1(1):4--25, 2006.

Digital Library

[6]

M. S. Manasse, L. A. McGeoch, and D. D. Sleator. Competitive algorithms for server problems. J. Algorithms, 11(2):208--230, 1990.

Digital Library

[7]

J. M. O'Kane and S. M. LaValle. On comparing the power of robots. International Journal of Robotics Research, 27(1):5--23, January 2008.

Digital Library

[8]

E. Osherovich, A. M. Bruckstein, and V. Yanovski. Covering a continuous domain by distributed, limited robots. In ANTS Workshop, pages 144--155, 2006.

Digital Library

[9]

G. Prencipe. CORDA: Distributed coordination of a set of autonomous mobile robots. In ERSADS, pages 185--190, May 2001.

[10]

R. Russell. Heat trails as short-lived navigational markers for mobile robots. In ICRA, volume 4, pages 3534--3539, 1997.

[11]

R. Russell. Ant trails: An example for robots to follow? In ICRA, volume 4, pages 2698--2703, 1999.

[12]

A. J. Sharkey. Robots, insects and swarm intelligence. Artificial Intelligence Review, 26(4):255--268, 2006.

Digital Library

[13]

M. Sipser. Introduction to the Theory of Computation. International Thomson Publishing, 1996.

Digital Library

[14]

I. Suzuki and M. Yamashita. Distributed anonymous mobile robots: Formation of geometric patterns. SIAM Journal on Computing, 28:1347--1363, 1999.

Digital Library

[15]

R. M. Turner. The tragedy of the commons and distributed AI systems. In in Proceedings of the 12th International Workshop on Distributed Artificial Intelligence, pages 379--390, 1993.

[16]

I. Wagner, M. Lindenbaum, and A. Bruckstein. Distributed covering by ant-robots using evaporating traces. IEEE Transactions on Robotics and Automation, 15(5):918--933, 1999.

[17]

I. A. Wagner, Y. Altshuler, V. Yanovski, and A. M. Bruckstein. Cooperative cleaners: A study in ant robotics. International Journal of Robotics Research, 27(1):127--151, 2008.

Digital Library

[18]

I. A. Wagner and A. M. Bruckstein. From ants to a(ge)nts: A special issue on ant-robotics (editorial). Annals of Mathematics and Artificial Intelligence, 31(1--4):1--5, 2001.

Digital Library

[19]

V. Yanovski, I. A. Wagner, and A. M. Bruckstein. Vertex-ant-walk: A robust method for efficient exploration of faulty graphs. Annals of Mathematics and Artificial Intelligence, 31(1--4):99--112, 2001.

Digital Library

Cited By

Sturtevant NBulitko VBjörnsson YLuck MSen S(2010)On learning in agent-centered searchProceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 110.5555/1838206.1838253(333-340)Online publication date: 10-May-2010
https://dl.acm.org/doi/10.5555/1838206.1838253
Shiloni ALevy AFelner AKalech MLuck MSen S(2010)Ants meeting algorithmsProceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 2 - Volume 210.5555/1838178.1838181(567-574)Online publication date: 10-May-2010
https://dl.acm.org/doi/10.5555/1838178.1838181

Index Terms

Of robot ants and elephants
1. Computing methodologies
  1. Artificial intelligence
    1. Distributed artificial intelligence
      1. Multi-agent systems
2. Theory of computation
  1. Models of computation

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Information & Contributors

Information

Published In

cover image Guide Proceedings

AAMAS '09: Proceedings of The 8th International Conference on Autonomous Agents and Multiagent Systems - Volume 1

May 2009

701 pages

ISBN:9780981738161

General Chairs:
Carles Sierra
Artificial Intelligence Research Institute of the Spanish Research Council (Spain)
,
Cristiano Castelfranchi
ISTC-CNR (Italy)
,
Program Chairs:
Keith S. Decker
University of Delaware
,
Jaime Simão Sichman
Politecnic School, University of São Paulo (Brazil)

Sponsors

Drexel University
Wiley-Blackwell
Microsoft Research: Microsoft Research
Whitestein Technologies
European Office of Aerospace Research and Development, Air Force Office of Scientific Research, United States Air Force Research Laboratory
The Foundation for Intelligent Physical Agents

Publisher

International Foundation for Autonomous Agents and Multiagent Systems

Richland, SC

Publication History

Published: 10 May 2009

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AAMAS '09 Paper Acceptance Rate 132 of 651 submissions, 20%;

Overall Acceptance Rate 1,155 of 5,036 submissions, 23%

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Cited By

Sturtevant NBulitko VBjörnsson YLuck MSen S(2010)On learning in agent-centered searchProceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 1 - Volume 110.5555/1838206.1838253(333-340)Online publication date: 10-May-2010
https://dl.acm.org/doi/10.5555/1838206.1838253
Shiloni ALevy AFelner AKalech MLuck MSen S(2010)Ants meeting algorithmsProceedings of the 9th International Conference on Autonomous Agents and Multiagent Systems: volume 2 - Volume 210.5555/1838178.1838181(567-574)Online publication date: 10-May-2010
https://dl.acm.org/doi/10.5555/1838178.1838181

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