Temat: Markov Decision Process (MDP) - Katalog OPAC zbiorów

Skocz do pozycji: 1.

Tytuł:: Optimal stopping model with unknown transition probabilities
Autorzy:: Horiguchi, M.
Piunovskiy, A. B.
Powiązania:: https://bibliotekanauki.pl/articles/205727.pdf
Data publikacji:: 2013
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: Markov Decision Process (MDP) unknown transition matrices
dynamic programming
Bayesian method
optimal stopping
Opis:: This article concerns the optimal stopping problem for a discrete-time Markov chain with observable states, but with unknown transition probabilities. A stopping policy is graded via the expected total-cost criterion resulting from the non-negative running and terminal costs. The Dynamic Programming method, combined with the Bayesian approach, is developed. A series of explicitly solved meaningful examples illustrates all the theoretical issues.
Źródło:: Control and Cybernetics; 2013, 42, 3; 593-612
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 2.

Tytuł:: Dynamic programming in constrained Markov decision
Autorzy:: Piunovskiy, A. B.
Powiązania:: https://bibliotekanauki.pl/articles/970861.pdf
Data publikacji:: 2006
Wydawca:: Polska Akademia Nauk. Instytut Badań Systemowych PAN
Tematy:: optymalizacja
programowanie dynamiczne
system kolejek
Markov decision process (MDP)
constraints
optimization
dynamic programming
myopic control strategy
queuing system
Opis:: We consider a discounted Markov Decision Process (MDP) supplemented with the requirement that another discounted loss must not exceed a specified value, almost surely. We show that he problem can be reformulated as a standard MDP and solved using the Dynamic Programming approach. An example on a controlled queue is presented. In the last section, we briefly reinforce the connection of the Dynamic Programming approach to another close problem statement and present the corresponding example. Several other types of constraints are discussed, as well.
Źródło:: Control and Cybernetics; 2006, 35, 3; 645-660
0324-8569
Pojawia się w:: Control and Cybernetics
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 3.

Tytuł:: Reinforcement Learning in Ship Handling
Autorzy:: Łącki, M.
Powiązania:: https://bibliotekanauki.pl/articles/117361.pdf
Data publikacji:: 2008
Wydawca:: Uniwersytet Morski w Gdyni. Wydział Nawigacyjny
Tematy:: Ship Handling
Reinforcement Learning
Machine Learning Techniques
Manoeuvring
Restricted Waters
Markov Decision Process (MDP)
Artificial Neural Network (ANN)
multi-agent environment
Opis:: This paper presents the idea of using machine learning techniques to simulate and demonstrate learning behaviour in ship manoeuvring. Simulated model of ship is treated as an agent, which through environmental sensing learns itself to navigate through restricted waters selecting an optimum trajectory. Learning phase of the task is to observe current state and choose one of the available actions. The agent gets positive reward for reaching destination and negative reward for hitting an obstacle. Few reinforcement learning algorithms are considered. Experimental results based on simulation program are presented for different layouts of possible routes within restricted area.
Źródło:: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation; 2008, 2, 2; 157-160
2083-6473
2083-6481
Pojawia się w:: TransNav : International Journal on Marine Navigation and Safety of Sea Transportation
Dostawca treści:: Biblioteka Nauki

Artykuł

Skocz do pozycji: 4.

Tytuł:: Markov Decision Process based Model for Performance Analysis an Intrusion Detection System in IoT Networks
Autorzy:: Kalnoor, Gauri
Gowrishankar, -
Powiązania:: https://bibliotekanauki.pl/articles/1839336.pdf
Data publikacji:: 2021
Wydawca:: Instytut Łączności - Państwowy Instytut Badawczy
Tematy:: DDoS
intrusion detection
IoT
machine learning
Markov decision process
MDP
Q-learning
NSL-KDD
reinforcement learning
Opis:: In this paper, a new reinforcement learning intrusion detection system is developed for IoT networks incorporated with WSNs. A research is carried out and the proposed model RL-IDS plot is shown, where the detection rate is improved. The outcome shows a decrease in false alarm rates and is compared with the current methodologies. Computational analysis is performed, and then the results are compared with the current methodologies, i.e. distributed denial of service (DDoS) attack. The performance of the network is estimated based on security and other metrics.
Źródło:: Journal of Telecommunications and Information Technology; 2021, 3; 42-49
1509-4553
1899-8852
Pojawia się w:: Journal of Telecommunications and Information Technology
Dostawca treści:: Biblioteka Nauki

Artykuł

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