Sökning: "Multi-agent-system"

Visar resultat 11 - 15 av 62 uppsatser innehållade ordet Multi-agent-system.

1. 11. Optimal Path Planning for Aerial Swarm in Area Exploration

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Johanna Norén; [2022]
   Nyckelord :Optimization; Path planning; Dynamic programming; Area exploration; Aerial swarm; Multi-agent system; Optimering; Ruttplanering; Dynamisk programmering; Områdesutforskning; Drönarsvärm; Fler-agentsfall;

   Sammanfattning : This thesis presents an approach to solve an optimal path planning problem for a swarm of drones. We optimize and improve information retrieval in area exploration within applications such a ‘Search and Rescue’-missions or reconnaissance missions. For this, dynamic programming has been used as a solving approach for a optimization problem. LÄS MER

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

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

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

   Sammanfattning : 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. LÄS MER

4. 13. A model checking tool for dynamic multi-agent systems

   Master-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Ye Leng; [2022]
   Nyckelord :;

   Sammanfattning : A multi-agent system (MAS) is a system composed of multiple interacting agents which can perform actions in a competitive environment. Among the theoretical framework which model MAS, we focus on named homogeneous and dynamic multi-agent system (HDMAS) first presented in [1]. HDMAS has two significant features: 1. LÄS MER

5. 14. Modelling Financial Markets via Multi-Agent Reinforcement Learning : How nothing interesting happened when I made AI trade with AI

   Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Mikołaj Bocheński; [2022]
   Nyckelord :Financial markets; Reinforcement learning; Multi-agent systems; Deep learning; Finansiella marknader; Förstärkningsinlärning; Multi-agent system; Djupinlärning;

   Sammanfattning : The numerous previous attempts to simulate financial markets tended to be based on strong assumptions about markets or their participants. This thesis describes a more general kind of model - one in which deep reinforcement learning is used to train agents to make a profit while trading with each other on a virtual exchange. LÄS MER

7. 15. Search methods for Strategy Synthesis for Multi-Agent Games of Imperfect Information

   Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)

   Författare :Axel Jernbäcker; Max Junestrand; [2021]
   Nyckelord :;

   Sammanfattning : Finding strategies for agents in multi-agent systems of imperfect information is a difficult and time-consuming endeavor. It is thus of interest to find ways of doing this more effectively. This study aims to improve the performance of a strategy synthesizer tool by testing two search techniques and evaluating their performance. LÄS MER