The classification of coverings of processor networks
Journal of Parallel and Distributed Computing
Piecemeal Learning of an Unknown Environment
Machine Learning - Special issue on COLT '93
Computing on Anonymous Networks: Part I-Characterizing the Solvable Cases
IEEE Transactions on Parallel and Distributed Systems
Information Processing Letters
Exploring Unknown Environments
SIAM Journal on Computing
Discrete Mathematics
The power of a pebble: exploring and mapping directed graphs
Information and Computation
An Effective Characterization of Computability in Anonymous Networks
DISC '01 Proceedings of the 15th International Conference on Distributed Computing
A Characterization of Families of Graphs in Which Election Is Possible
FoSSaCS '02 Proceedings of the 5th International Conference on Foundations of Software Science and Computation Structures
Local and global properties in networks of processors (Extended Abstract)
STOC '80 Proceedings of the twelfth annual ACM symposium on Theory of computing
Labeling Schemes for Flow and Connectivity
SIAM Journal on Computing
Journal of Algorithms
Journal of the ACM (JACM)
Optimal graph exploration without good maps
Theoretical Computer Science
Compact Labeling Scheme for Ancestor Queries
SIAM Journal on Computing
Oracle size: a new measure of difficulty for communication tasks
Proceedings of the twenty-fifth annual ACM symposium on Principles of distributed computing
An Efficient Message Passing Election Algorithm based on Mazurkiewicz's Algorithm
Fundamenta Informaticae - Half a Century of Inspirational Research: Honoring the Scientific Influence of Antoni Mazurkiewicz
Trade-offs between the size of advice and broadcasting time in trees
Proceedings of the twentieth annual symposium on Parallelism in algorithms and architectures
Journal of Graph Theory
Label-guided graph exploration by a finite automaton
ACM Transactions on Algorithms (TALG)
Undirected connectivity in log-space
Journal of the ACM (JACM)
Information and Computation
Theoretical Computer Science
Online Computation with Advice
ICALP '09 Proceedings of the 36th International Colloquium on Automata, Languages and Programming: Part I
Fast radio broadcasting with advice
Theoretical Computer Science
How to meet when you forget: log-space rendezvous in arbitrary graphs
Proceedings of the 29th ACM SIGACT-SIGOPS symposium on Principles of distributed computing
Local MST Computation with Short Advice
Theory of Computing Systems - Special Title: Parallelism on Algorithms and Architectures (SPAA); Guest Editors: Cyril Gavoille, Boaz Patt-Shamir and Christian Scheideler
Online graph exploration with advice
SIROCCO'12 Proceedings of the 19th international conference on Structural Information and Communication Complexity
Randomized distributed decision
DISC'12 Proceedings of the 26th international conference on Distributed Computing
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We study the problem of the amount of information required to draw a complete or a partial map of a graph with unlabeled nodes and arbitrarily labeled ports. A mobile agent, starting at any node of an unknown connected graph and walking in it, has to accomplish one of the following tasks: draw a complete map of the graph, i.e., find an isomorphic copy of it including port numbering, or draw a partial map, i.e., a spanning tree, again with port numbering. The agent executes a deterministic algorithm and cannot mark visited nodes in any way. None of these map drawing tasks is feasible without any additional information, unless the graph is a tree. Hence we investigate the minimum number of bits of information (minimum size of advice) that has to be given to the agent to complete these tasks. It turns out that this minimum size of advice depends on the number n of nodes or the number m of edges of the graph, and on a crucial parameter @m, called the multiplicity of the graph, which measures the number of nodes that have an identical view of the graph. We give bounds on the minimum size of advice for both above tasks. For @m=1 our bounds are asymptotically tight for both tasks and show that the minimum size of advice is very small. For @m1 the minimum size of advice increases abruptly. In this case our bounds are asymptotically tight for topology recognition and asymptotically almost tight for spanning tree construction.