PENJADWALAN PENGAMATAN DENGAN ALGORITMA REINFORCEMENT LEARNING
The first step before doing observation is to decide objects, location, and time for observing. After the first step is fulfilled and approved, the next step is determining observation duration for each objects according to sets of priority. This step is called observational scheduling. Observationa...
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id-itb.:660032022-06-26T14:51:58ZPENJADWALAN PENGAMATAN DENGAN ALGORITMA REINFORCEMENT LEARNING Mario Slamet Prakos, Vincentius Indonesia Final Project Observational scheduling, Real-time data set, Reinforcement Learning INSTITUT TEKNOLOGI BANDUNG https://digilib.itb.ac.id/gdl/view/66003 The first step before doing observation is to decide objects, location, and time for observing. After the first step is fulfilled and approved, the next step is determining observation duration for each objects according to sets of priority. This step is called observational scheduling. Observational scheduling can make use of real time data set. Reinforcement Learning (RL) is an area of Machine Learning related to interaction between Agent and Environment to produce optimal Actions. RL algorithm can be used to process real-time data set. Accordingly, RL algorithm too can be used for determining optimal observational scheduling. text |
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Institut Teknologi Bandung |
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Institut Teknologi Bandung Library |
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Asia |
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Indonesia Indonesia |
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Institut Teknologi Bandung |
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Digital ITB |
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Indonesia |
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The first step before doing observation is to decide objects, location, and time for observing. After the first step is fulfilled and approved, the next step is determining observation duration for each objects according to sets of priority. This step is called observational scheduling. Observational scheduling can make use of real time data set. Reinforcement Learning (RL) is an area of Machine Learning related to interaction between Agent and Environment to produce optimal Actions. RL algorithm can be used to process real-time data set. Accordingly, RL algorithm too can be used for determining optimal observational scheduling. |
| format |
Final Project |
| author |
Mario Slamet Prakos, Vincentius |
| spellingShingle |
Mario Slamet Prakos, Vincentius PENJADWALAN PENGAMATAN DENGAN ALGORITMA REINFORCEMENT LEARNING |
| author_facet |
Mario Slamet Prakos, Vincentius |
| author_sort |
Mario Slamet Prakos, Vincentius |
| title |
PENJADWALAN PENGAMATAN DENGAN ALGORITMA REINFORCEMENT LEARNING |
| title_short |
PENJADWALAN PENGAMATAN DENGAN ALGORITMA REINFORCEMENT LEARNING |
| title_full |
PENJADWALAN PENGAMATAN DENGAN ALGORITMA REINFORCEMENT LEARNING |
| title_fullStr |
PENJADWALAN PENGAMATAN DENGAN ALGORITMA REINFORCEMENT LEARNING |
| title_full_unstemmed |
PENJADWALAN PENGAMATAN DENGAN ALGORITMA REINFORCEMENT LEARNING |
| title_sort |
penjadwalan pengamatan dengan algoritma reinforcement learning |
| url |
https://digilib.itb.ac.id/gdl/view/66003 |
| _version_ |
1822277497736134656 |