Sökning: "Förstärkande inlärning"
Visar resultat 21 - 25 av 35 uppsatser innehållade orden Förstärkande inlärning.
21. Interference Aware Distributed Network Formation with Reinforcement Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Ad-hoc networks suffer from dynamicity due to mobility of the nodes or node addition/removal to/from the system. This means, the formed topology may not be connected anymore or better topologies can be found as time passes if the position of the nodes changes or some nodes in the network is broken. LÄS MER
22. A deep reinforcement learning approach to the problem of golf using an agent limited by human data
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : In the sport of golf, the use of statistics has become prominent as a way of understanding and improving golfers’ golf swings. Even though swing data is easily accessible thanks to a variety of technological tools, it is not always clear how to use this data, especially for amateur golfers. LÄS MER
23. Scheduling using Deep Reinforcement Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : As radio networks have continued to evolve in recent decades, so have theircomplexity and the difficulty in efficiently utilizing the available resources. Ina cellular network, the scheduler controls the allocation of time, frequencyand spatial resources to users in both uplink and downlink directions. LÄS MER
24. On Optimization of Sequential Decision-Making in Customer Relationship Management using Deep Reinforcement Learning
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Customer relationship management (CRM) is a fickle but pivotal elementto the success of any business. Used correctly, it can not only yield higherrevenue and lower operational costs, but significantly boost customersatisfaction. Nonetheless, it can also be mismanaged—sacrificing thewell-being of customers for profitability. LÄS MER
25. DQN Tackling the Game of Candy Crush Friends Saga : A Reinforcement Learning Approach
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : This degree project presents a reinforcement learning (RL) approach called deep Q-network (DQN) for learning how to play the game Candy Crush Friends Saga (CCFS). The DQN algorithm is implemented together with three extensions, which in 2015 resulted in a new state-of-the-art on the Atari 2600 domain. LÄS MER
