Essays about: "Deep Q-Networks"

Showing result 1 - 5 of 12 essays containing the words Deep Q-Networks.

1. 1. Reinforcement Learning for Multi-Agent Strategy Synthesis Using Higher-Order Knowledge

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Gustav Forsell; Shamoun Gergi; [2023]
   Keywords : Higher Order Knowledge; Imperfect Information; Reinforcement Learning; Deep Q- networks; Knowledge Representation; Pursuit Evasion Games;

   Abstract : Imagine for a moment we are living in the distant future where autonomous robots are patrollingthe streets as police officers. Two such robots are chasing a robber through the city streets. Fearingthe thief might listen in to any potential transmission, both robots remain radio silent and are thuslimited to a strictly visual pursuit. READ MORE

3. 2. Scalable Deep Reinforcement Learning for a Multi-Agent Warehouse System

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Akib Khan; Marcus Loberg; [2022]
   Keywords : Reinforcement learning; Deep Q Networks; Neural Network; Scalability; Multi-Agents; Warehouse Environment;

   Abstract : This report presents an application of reinforcementlearning to the problem of controlling multiple robots performingthe task of moving boxes in a warehouse environment. The robotsmake autonomous decisions individually and avoid colliding witheach other and the walls of the warehouse. READ MORE

4. 3. Investigating Multi-Objective Reinforcement Learning for Combinatorial Optimization and Scheduling Problems : Feature Identification for multi-objective Reinforcement Learning models

   University essay from KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Author : Rikard Fridsén Skogsberg; [2022]
   Keywords : Multi-Objective Reinforcement Learning; Radio Resource Scheduling; Deep Q-Networks; Single-policy; Multi-policy; Scalarization.; Flermåls förstärkningsinlärning; Radio resurs schemaläggning; Djupa Q-nätverk; Enskilt mål; Flermål;

   Abstract : Reinforcement Learning (RL) has in recent years become a core method for sequential decision making in complex dynamical systems, being of great interest to support improvements in scheduling problems. This could prove important to areas in the newer generation of cellular networks. READ MORE

5. 4. Solving Tetris-like Puzzles with Informed Search and Machine Learning

   University essay from Linköpings universitet/Medie- och Informationsteknik; Linköpings universitet/Tekniska fakulteten

   Author : Anneli Nilsson; [2021]
   Keywords : Informed search; Machine learning; Reinforcement learing; Puzzle solving;

   Abstract : Assembling different kinds of items, everything from furniture to hobby models, takes a certain process to complete and this process can vary in complexity. An interesting aspect of this process is what components are available during assembly. READ MORE

6. 5. Offline Reinforcement Learning for Remote Electrical Tilt Optimization : An application of Conservative Q-Learning

   University essay from KTH/Matematik (Avd.)

   Author : Marcus Kastengren; [2021]
   Keywords : Remote Electrical Tilt; Antenna Tilt Optimization; Reinforcement Learning; Offline Reinforcement Learning; Conservative Q-Learning; Fjärrlutning; Antennlutningsoptimering; Förstärkningsinlärning; Offline-förstärkningsinlärning; Konservativ Q-inlärning;

   Abstract : In telecom networks adjusting the tilt of antennas in an optimal manner, the so called remote electrical tilt (RET) optimization, is a method to ensure quality of service (QoS) for network users. Tilt adjustments made during operations in real-world networks are usually executed through a suboptimal policy, and a significant amount of data is collected during the execution of such policy. READ MORE