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Record Nr. |
UNINA9910797798303321 |
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Autore |
Cecchetto Carlo |
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Titolo |
(Re)labeling [[electronic resource] /] / Carlo Cecchetto & Caterina Donati |
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Pubbl/distr/stampa |
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Cambridge, Mass., : The MIT Press, 2015 |
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ISBN |
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9780262327220 : (ebk : EbookCentral) |
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Descrizione fisica |
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Altri autori (Persone) |
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Disciplina |
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Soggetti |
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Grammar, Comparative and general - Syntax |
Parallelism (Linguistics) |
Generative grammar |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Note generali |
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Bibliographic Level Mode of Issuance: Monograph |
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Nota di bibliografia |
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Includes bibliographical references and index. |
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2. |
Record Nr. |
UNINA9910346889403321 |
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Autore |
Krauthausen Peter |
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Titolo |
Learning Dynamic Systems for Intention Recognition in Human-Robot-Cooperation |
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Pubbl/distr/stampa |
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KIT Scientific Publishing, 2013 |
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ISBN |
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Descrizione fisica |
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1 online resource (XIV, 210 p. p.) |
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Collana |
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Karlsruhe Series on Intelligent Sensor-Actuator-Systems / Karlsruher Institut für Technologie, Intelligent Sensor-Actuator-Systems Laboratory |
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Lingua di pubblicazione |
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Formato |
Materiale a stampa |
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Livello bibliografico |
Monografia |
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Sommario/riassunto |
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This thesis is concerned with intention recognition for a humanoid robot and investigates how the challenges of uncertain and incomplete observations, a high degree of detail of the used models, and real-time inference may be addressed by modeling the human rationale as hybrid, dynamic Bayesian networks and performing inference with these models. The key focus lies on the automatic identification of the employed nonlinear stochastic dependencies and the situation-specific inference. |
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