Object
Title: Knowledge-Based Solvers for RGT Combinatorial Problems
Co-author(s) :
Hakobyan Nairi ; Baghdasaryan Tadevos
Abstract:
In this work, we present means for usage of RGT (Reproducible Game Trees) Solvers, that include knowledge acquisition, matching and decision making algorithms for RGT problems. The RGT Solvers are being regularly improved and the current implementation tries to cover the drawbacks of previous versions, improves presentation of classifiers and mental doings, as well as provides enhancements in interface. We also discuss ways of knowledge acquisition for marketing and battlefield problems by RGT Solvers.
Identifier:
oai:noad.sci.am:136206
DOI:
10.1109/CSITechnol.2019.8895131
ISBN:
Language:
URL:
Affiliation:
Division of Computational and Cognitive networks ; Institute for Informatics and Automation Problems of NAS RA ; Department of System Programming RAU
Year:
Time period:
Conference title:
2019 Computer Science and Information Technologies (CSIT)
Place:
Object collections:
- Digital Library > Academic Insitutions > Insitute for Informatics and Automation Problems of NAS RA > Conferences
Last modified:
May 3, 2021
In our library since:
Apr 30, 2021
Number of object content hits:
19
All available object's versions:
https://noad.sci.am/publication/149771
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Show description in OAI-PMH format:
| Edition name | Date |
|---|---|
| Grigoryan Sedrak, Knowledge-Based Solvers for RGT Combinatorial Problems | May 3, 2021 |
