Abstract
In Mutual Search, recently introduced by Buhrman et al. (1998), static agents are searching for each other: each agent is assigned one of n locations, and the computations proceed by agents sending queries from their location to other locations, until one of the queries arrives at the other agent. The cost of a search is the number of queries made. The best known bounds for randomized protocols using private coins are (1) a protocol with worst-case expected cost of [(n + 1)/2], and (2) a lower bound of (n - 1)/8 queries for randomized protocols which make only a bounded number of coin-tosses. In this paper we strictly improve the lower bound, and present a new upper bound for shared random coins. Specifically, we first prove that the worst-case expected cost of any randomized protocol for two-agent mutual search is at least (n + 1)/3. This is an improvement both in terms of number of queries and in terms of applicability. We also give a randomized algorithm for mutual search with worst-case expected cost of (n + 1)/3. This algorithm works under the assumption that the agents share a random bit string. This bound shows that no better lower bound can be obtained using our technique.
| Original language | English |
|---|---|
| Pages (from-to) | 187-191 |
| Number of pages | 5 |
| Journal | Information Processing Letters |
| Volume | 71 |
| Issue number | 5-6 |
| DOIs | |
| State | Published - 30 Sep 1999 |
| Externally published | Yes |
Bibliographical note
Funding Information:I Research partially supported by a grant from Israel Ministry of Science and Technology. ∗Corresponding author. Email: [email protected]. 1Email: [email protected]. 2In [1], a general case of k agents operating in an asynchronous environment is defined too. In this note we focus on the basic synchronous two-agent case, which seems to represent the combinatorial difficulty of the problem.
Funding
I Research partially supported by a grant from Israel Ministry of Science and Technology. ∗Corresponding author. Email: [email protected]. 1Email: [email protected]. 2In [1], a general case of k agents operating in an asynchronous environment is defined too. In this note we focus on the basic synchronous two-agent case, which seems to represent the combinatorial difficulty of the problem.
| Funders |
|---|
| Ministry of science and technology, Israel |
Keywords
- Algorithms
- Lower bound
- Randomized algorithms
- Two-agent mutual search
- Upper bound
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