Hybrid fuzzy AHP–TOPSIS approach to prioritizing solutions for inverse reinforcement learning
Abstract Reinforcement learning (RL) techniques nurture building up solutions for sequential decision-making problems under uncertainty and ambiguity. RL has agents with a reward function that interacts with a dynamic environment to find out an optimal policy. There are problems associated with RL l...
Main Author: | Vinay Kukreja |
---|---|
Format: | Article |
Language: | English |
Published: |
Springer
2022-07-01
|
Series: | Complex & Intelligent Systems |
Subjects: | |
Online Access: | https://doi.org/10.1007/s40747-022-00807-5 |
Similar Items
-
Comprehensive Assessment of Distance Learning Modules by Fuzzy AHP-TOPSIS Method
by: Svajone Bekesiene, et al.
Published: (2021-02-01) -
Comparing fuzzy AHP and fuzzy TOPSIS for evaluation of business intelligence vendors
by: Alireza Soloukdar, et al.
Published: (2015-04-01) -
AN INTEGRATED FUZZY AHP AND TOPSIS MODEL FOR SUPPLIER EVALUATION
by: Željko Stević, et al.
Published: (2016-05-01) -
Pemilihan Green Supplier Berdasarkan Fuzzy AHP Dengan Metode Fuzzy Topsis
by: Akhmad Ghiffary Budianto
Published: (2017-05-01) -
Integrasi Fuzzy AHP-TOPSIS dalam Evaluasi Kualitas Layanan Elektronik Rumah Sakit
by: Ronald Sukwadi, et al.
Published: (2014-01-01)