Access the full text.
Sign up today, get DeepDyve free for 14 days.
J. Hopcroft, R. Tarjan (1973)
Algorithm 447: efficient algorithms for graph manipulationCommun. ACM, 16
A. Fraenkel (1970)
Economic Traversal of LabyrinthsMathematics Magazine, 43
J. Hopcroft, R. Tarjan (1971)
Efficient algorithms for graph manipulation
S. Thrun (1992)
Eecient Exploration in Reinforcement Learning
C. Goldman, J. Rosenschein (1994)
Emergent Coordination through the Use of Cooperative State-Changing Rules
I. Wagner, M. Lindenbaum, A. Bruckstein (1996)
Smell as a Computational Resource - A Lesson We Can Learn from the Ant
S. Even (1979)
Graph Algorithms
Nelson Beebe (2001)
Probability in the Engineering and Informational Sciences
M. Dorigo, V. Maniezzo, A. Colorni (1996)
The ant system: Optimization by a colony of cooperating agentsIEEE Trans. on Systems, Man, and Cybernetics – Part B, 26
R. Korf (1990)
Real-Time Heuristic SearchArtif. Intell., 42
R. Tarjan (1972)
Depth-First Search and Linear Graph AlgorithmsSIAM J. Comput., 1
(1970)
Mathematics Magazine
M. Blum, D. Kozen (1978)
On the power of the compass (or, why mazes are easier to search than graphs)19th Annual Symposium on Foundations of Computer Science (sfcs 1978)
S. Thrun (1992)
The role of exploration in learning control
A. Broder, Anna Karlin, P. Raghavan, E. Upfal (1989)
Trading space for time in undirected s-t connectivitySIAM J. Comput., 23
R. Aleliunas, R. Karp, R. Lipton, L. Lovász, C. Rackoff (1979)
Random walks, universal traversal sequences, and the complexity of maze problems20th Annual Symposium on Foundations of Computer Science (sfcs 1979)
M. Dorigo, V. Maniezzo, A. Colorni (1996)
Ant system: optimization by a colony of cooperating agentsIEEE transactions on systems, man, and cybernetics. Part B, Cybernetics : a publication of the IEEE Systems, Man, and Cybernetics Society, 26 1
Sven Koenig, Y. Smirnov (1996)
Graph learning with a nearest neighbor approach
S. Gal, E. Anderson (1990)
Search in a MazeProbability in the Engineering and Informational Sciences, 4
G. Barnes, U. Feige (1993)
Short random walks on graphsProceedings of the twenty-fifth annual ACM symposium on Theory of Computing
TracesIsrael Wagner (1996)
Cooperative Covering by Ant-Robots using Evaporating
(1895)
Le problem des labyrinths
R. Jewett, K. Ross (1988)
Random Walks on ℤCollege Mathematics Journal, 19
Jabib Sanchez (2006)
THE SELF-AVOIDING WALK
(1979)
Graph Algorithms (Computer Science Press, Rockville, MD, 1979)
S. Bhatt, S. Even, D. Greenberg, R. Tayar
Journal of Graph Algorithms and Applications Traversing Directed Eulerian Mazes
Efficient graph search is a central issue in many aspects of AI. In most of existing work there is a distinction between the active “searcher”, which both executes the algorithm and holds the memory, and the passive “searched graph”, over which the searcher has no control at all. Large dynamic networks like the Internet, where the nodes are powerful computers and the links have narrow bandwidth and are heavily-loaded, call for a different paradigm, in which most of the burden of computing and memorizing is moved from the searching agent to the nodes of the network. In this paper we suggest a method for searching an undirected, connected graph using the Vertex-Ant-Walk method, where an a(ge)nt walks along the edges of a graph G, occasionally leaving “pheromone” traces at nodes, and using those traces to guide its exploration. We show that the ant can cover the graph within time O(nd), where n is the number of vertices and d the diameter of G. The use of traces achieves a trade-off between random and self-avoiding walks, as it dictates a lower priority for already-visited neighbors. Further properties of the suggested method are: (a) modularity: a group of searching agents, each applying the same protocol, can cooperate on a mission of covering a graph with minimal explicit communication between them; (b) possible convergence to a limit cycle: a Hamiltonian path in G (if one exists) is a possible limit cycle of the process.
Annals of Mathematics and Artificial Intelligence – Springer Journals
Published: Oct 23, 2004
Read and print from thousands of top scholarly journals.
Already have an account? Log in
Bookmark this article. You can see your Bookmarks on your DeepDyve Library.
To save an article, log in first, or sign up for a DeepDyve account if you don’t already have one.
Copy and paste the desired citation format or use the link below to download a file formatted for EndNote
Access the full text.
Sign up today, get DeepDyve free for 14 days.
All DeepDyve websites use cookies to improve your online experience. They were placed on your computer when you launched this website. You can change your cookie settings through your browser.