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Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach
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| Zeitschriftentitel: | Theory and Practice of Logic Programming |
|---|---|
| Personen und Körperschaften: | , , , , |
| In: | Theory and Practice of Logic Programming, 13, 2013, 4-5, S. 831-846 |
| Format: | E-Article |
| Sprache: | Englisch |
| veröffentlicht: |
Cambridge University Press (CUP)
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| Schlagwörter: |
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ERDEM, ESRA PATOGLU, VOLKAN SARIBATUR, ZEYNEP G. SCHÜLLER, PETER URAS, TANSEL ERDEM, ESRA PATOGLU, VOLKAN SARIBATUR, ZEYNEP G. SCHÜLLER, PETER URAS, TANSEL |
|---|---|
| author |
ERDEM, ESRA PATOGLU, VOLKAN SARIBATUR, ZEYNEP G. SCHÜLLER, PETER URAS, TANSEL |
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ERDEM, ESRA PATOGLU, VOLKAN SARIBATUR, ZEYNEP G. SCHÜLLER, PETER URAS, TANSEL Theory and Practice of Logic Programming Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach Artificial Intelligence Computational Theory and Mathematics Hardware and Architecture Theoretical Computer Science Software |
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ERDEM, ESRA PATOGLU, VOLKAN SARIBATUR, ZEYNEP G. SCHÜLLER, PETER URAS, TANSEL 1471-0684 1475-3081 Cambridge University Press (CUP) Artificial Intelligence Computational Theory and Mathematics Hardware and Architecture Theoretical Computer Science Software http://dx.doi.org/10.1017/s1471068413000525 <jats:title>Abstract</jats:title><jats:p>We study the problem of finding optimal plans for multiple teams of robots through a mediator, where each team is given a task to complete in its workspace on its own and where teams are allowed to transfer robots between each other, subject to the following constraints: 1) teams (and the mediator) do not know about each other's workspace or tasks (e.g., for privacy purposes); 2) every team can lend or borrow robots, but not both (e.g., transportation/calibration of robots between/for different workspaces is usually costly). We present a mathematical definition of this problem and analyze its computational complexity. We introduce a novel, logic-based method to solve this problem, utilizing action languages and answer set programming for representation, and the state-of-the-art ASP solvers for reasoning. We show the applicability and usefulness of our approach by experiments on various scenarios of responsive and energy-efficient cognitive factories.</jats:p> Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach Theory and Practice of Logic Programming |
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Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
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Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
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Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
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Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
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Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
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Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
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finding optimal plans for multiple teams of robots through a mediator: a logic-based approach |
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Artificial Intelligence Computational Theory and Mathematics Hardware and Architecture Theoretical Computer Science Software |
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2013 |
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<jats:title>Abstract</jats:title><jats:p>We study the problem of finding optimal plans for multiple teams of robots through a mediator, where each team is given a task to complete in its workspace on its own and where teams are allowed to transfer robots between each other, subject to the following constraints: 1) teams (and the mediator) do not know about each other's workspace or tasks (e.g., for privacy purposes); 2) every team can lend or borrow robots, but not both (e.g., transportation/calibration of robots between/for different workspaces is usually costly). We present a mathematical definition of this problem and analyze its computational complexity. We introduce a novel, logic-based method to solve this problem, utilizing action languages and answer set programming for representation, and the state-of-the-art ASP solvers for reasoning. We show the applicability and usefulness of our approach by experiments on various scenarios of responsive and energy-efficient cognitive factories.</jats:p> |
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| author_facet | ERDEM, ESRA, PATOGLU, VOLKAN, SARIBATUR, ZEYNEP G., SCHÜLLER, PETER, URAS, TANSEL, ERDEM, ESRA, PATOGLU, VOLKAN, SARIBATUR, ZEYNEP G., SCHÜLLER, PETER, URAS, TANSEL |
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| description | <jats:title>Abstract</jats:title><jats:p>We study the problem of finding optimal plans for multiple teams of robots through a mediator, where each team is given a task to complete in its workspace on its own and where teams are allowed to transfer robots between each other, subject to the following constraints: 1) teams (and the mediator) do not know about each other's workspace or tasks (e.g., for privacy purposes); 2) every team can lend or borrow robots, but not both (e.g., transportation/calibration of robots between/for different workspaces is usually costly). We present a mathematical definition of this problem and analyze its computational complexity. We introduce a novel, logic-based method to solve this problem, utilizing action languages and answer set programming for representation, and the state-of-the-art ASP solvers for reasoning. We show the applicability and usefulness of our approach by experiments on various scenarios of responsive and energy-efficient cognitive factories.</jats:p> |
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| spelling | ERDEM, ESRA PATOGLU, VOLKAN SARIBATUR, ZEYNEP G. SCHÜLLER, PETER URAS, TANSEL 1471-0684 1475-3081 Cambridge University Press (CUP) Artificial Intelligence Computational Theory and Mathematics Hardware and Architecture Theoretical Computer Science Software http://dx.doi.org/10.1017/s1471068413000525 <jats:title>Abstract</jats:title><jats:p>We study the problem of finding optimal plans for multiple teams of robots through a mediator, where each team is given a task to complete in its workspace on its own and where teams are allowed to transfer robots between each other, subject to the following constraints: 1) teams (and the mediator) do not know about each other's workspace or tasks (e.g., for privacy purposes); 2) every team can lend or borrow robots, but not both (e.g., transportation/calibration of robots between/for different workspaces is usually costly). We present a mathematical definition of this problem and analyze its computational complexity. We introduce a novel, logic-based method to solve this problem, utilizing action languages and answer set programming for representation, and the state-of-the-art ASP solvers for reasoning. We show the applicability and usefulness of our approach by experiments on various scenarios of responsive and energy-efficient cognitive factories.</jats:p> Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach Theory and Practice of Logic Programming |
| spellingShingle | ERDEM, ESRA, PATOGLU, VOLKAN, SARIBATUR, ZEYNEP G., SCHÜLLER, PETER, URAS, TANSEL, Theory and Practice of Logic Programming, Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach, Artificial Intelligence, Computational Theory and Mathematics, Hardware and Architecture, Theoretical Computer Science, Software |
| title | Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
| title_full | Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
| title_fullStr | Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
| title_full_unstemmed | Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
| title_short | Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
| title_sort | finding optimal plans for multiple teams of robots through a mediator: a logic-based approach |
| title_unstemmed | Finding optimal plans for multiple teams of robots through a mediator: A logic-based approach |
| topic | Artificial Intelligence, Computational Theory and Mathematics, Hardware and Architecture, Theoretical Computer Science, Software |
| url | http://dx.doi.org/10.1017/s1471068413000525 |