Παρακαλώ χρησιμοποιήστε αυτό το αναγνωριστικό για να παραπέμψετε ή να δημιουργήσετε σύνδεσμο προς αυτό το τεκμήριο:
https://hdl.handle.net/20.500.14279/8206
Τίτλος: | A partially-observable markov decision process for dealing with dynamically changing environments | Συγγραφείς: | Chatzis, Sotirios P. Kosmopoulos, Dimitrios I. |
Major Field of Science: | Engineering and Technology | Field Category: | Computer and Information Sciences | Λέξεις-κλειδιά: | POMDP problem;Bayesian non-parametrics;Dirichlet process | Ημερομηνία Έκδοσης: | 2014 | Πηγή: | 10th International Conference on Artificial Intelligence Applications and Innovations, 2014, Rhodes, Greece, 19-21 September, pp. 111-120 | Conference: | IFIP WG 12.5 International Conference on Artificial Intelligence Applications and Innovations | Περίληψη: | This paper offers a solution to the non-stationary POMDP problem, by making use of methods and concepts from the field of Bayesian non-parametrics, specifically dynamic hierarchical Dirichlet process priors. We combine block Gibbs sampling and importance sampling to perform inference. We evaluate the method in several benchmark policy learning tasks | Description: | Part of the IFIP Advances in Information and Communication Technology book series (IFIPAICT, vol. 436). | URI: | https://hdl.handle.net/20.500.14279/8206 | ISBN: | 978-3-662-44654-6 (online) 978-3-662-44653-9 (print) |
DOI: | 10.1007/978-3-662-44654-6_11 | Type: | Conference Papers | Affiliation: | Cyprus University of Technology Hellenic Mediterranean University |
Εμφανίζεται στις συλλογές: | Δημοσιεύσεις σε συνέδρια /Conference papers or poster or presentation |
CORE Recommender
SCOPUSTM
Citations
50
1
checked on 6 Νοε 2023
Page view(s) 50
435
Last Week
0
0
Last month
5
5
checked on 6 Νοε 2024
Google ScholarTM
Check
Altmetric
Όλα τα τεκμήρια του δικτυακού τόπου προστατεύονται από πνευματικά δικαιώματα