Search results for: ALGORYTMY ONLINE

• Music Information Retrieval – Soft Computing versus Statistics . Wyszukiwanie informacji muzycznej - algorytmy uczące versus metody statystyczne

  Publication

  • B. Kostek

  - Year 2015

  Music Information Retrieval (MIR) is an interdisciplinary research area that covers automated extraction of information from audio signals, music databases and services enabling the indexed information searching. In the early stages the primary focus of MIR was on music information through Query-by-Humming (QBH) applications, i.e. on identifying a piece of music by singing (singing/whistling), while more advanced implementations...

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• Multi-agent graph searching and exploration algorithms

  Publication

  • D. Osula

  - Year 2020

  A team of mobile entities, which we refer to as agents or searchers interchangeably, starting from homebases needs to complete a given task in a graph.The goal is to build a strategy, which allows agents to accomplish their task. We analyze strategies for their effectiveness (e.g., the number of used agents, the total number of performed moves by the agents or the completion time).Currently, the fields of on-line (i.e., agents...

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• The maximum edge-disjoint paths problem in complete graphs

  Publication

  • A. Kosowski

  - THEORETICAL COMPUTER SCIENCE - Year 2008

  Rozważono problem ścieżek krawędziowo rozłącznych w grafach pełnych. Zaproponowano wielomianowe algorytmy: 3.75-przybliżony (off-line) oraz 6.47-przybliżony (on-line), poprawiając tym samym wyniki wcześniej znane z literatury [P. Carmi, T. Erlebach, Y. Okamoto, Greedy edge-disjoint paths in complete graphs, in: Proc. 29th Workshop on Graph Theoretic Concepts in Computer Science, in: LNCS, vol. 2880, 2003, pp. 143-155]. Ponadto...

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• Fast Collaborative Graph Exploration

  Publication

  • D. Dereniowski
  • Y. Disser
  • A. Kosowski
  • D. Pająk
  • P. Uznański

  - LECTURE NOTES IN COMPUTER SCIENCE - Year 2013

  We study the following scenario of online graph exploration. A team of k agents is initially located at a distinguished vertex r of an undirected graph. At every time step, each agent can traverse an edge of the graph. All vertices have unique identifiers, and upon entering a vertex, an agent obtains the list of identifiers of all its neighbors. We ask how many time steps are required to complete exploration, i.e., to make sure...

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