Sökning: "RL"

Visar resultat 21 - 25 av 132 uppsatser innehållade ordet RL.

1. 21. How does the performance of NEAT compare to Reinforcement Learning?

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

   Författare :Marcus Andersson; [2022]
   Nyckelord :;

   Sammanfattning : This study examined the relative performance of Deep Reinforcement Learning compared to a neuroevolution algorithm called NEAT when used to train AIs in a discrete game environment. Today there are many AI techniques to choose from among which NEAT and RL have become popular alternatives. LÄS MER

3. 22. Explainable Reinforcement Learning for Gameplay

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

   Författare :Àlex Costa Sánchez; [2022]
   Nyckelord :Explainable Artificial Intelligence; Local Interpretable Model-agnostic Explanations; Reinforcement Learning; Shapley Additive Explanations; Intel·ligencia Artificial Interpretable; Explicacions model-agnòstiques localment interpretables; Aprenentatge per reforç; Explicacions additives de Shapley; Förklarbar artificiell intelligent; Lokala tolkningsbara modellagnostiska förklaringar; Förstärkningsinlärning; Shapleys additiv förklaringar;

   Sammanfattning : State-of-the-art Machine Learning (ML) algorithms show impressive results for a myriad of applications. However, they operate as a sort of a black box: the decisions taken are not human-understandable. LÄS MER

4. 23. Modelling Cyber Security of Networks as a Reinforcement Learning Problem using Graphs : An Application of Reinforcement Learning to the Meta Attack Language

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

   Författare :Sandor Berglund; [2022]
   Nyckelord :Attack graphs; reinforcement learning; graph neural networks; Meta Attack Language; MAL; deepQ-learning DQN ; Attackgrafer; förstärningsinlärning; artificiella neuronnät; grafneuronnät; djup Qinlärning; Meta Attack Language; MAL;

   Sammanfattning : ICT systems are part of the vital infrastructure in today’s society. These systems are under constant threat and efforts are continually being put forth by cyber security experts to protect them. By applying modern AI methods, can these efforts both be improved and alleviated of the cost of expert work. LÄS MER

5. 24. Embracing AWKWARD! A Hybrid Architecture for Adjustable Socially-Aware Agents

   Master-uppsats, Umeå universitet/Institutionen för datavetenskap

   Författare :Leila Methnani; [2022]
   Nyckelord :;

   Sammanfattning : This dissertation presents AWKWARD: a hybrid architecture for the development of socially aware agents in Multi-Agent Systems (MAS). AWKWARD bridges Artificial Intelligence (AI) methods for their individual and combined strengths; Behaviour Oriented Design (BOD) is used to develop reactive planning agents, the OperA framework is used to modeland validate agent behaviour as per social norms, and Reinforcement Learning (RL) is used to optimise plan structures that induce desirable social outcomes. LÄS MER

7. 25. Link Adaptation in 5G Networks : Reinforcement Learning Framework based Approach

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

   Författare :Siva Satya Sri Ganesh Seeram; [2022]
   Nyckelord :Link Adaptation; OLLA; AMC; Reinforcement Learning; DDPG; BLER; Länkanpassning; OLLA; AMC; förstärkningsinlärning; DDPG; BLER;

   Sammanfattning : Link Adaptation is a core feature introduced in gNodeB (gNB) for Adaptive Modulation and Coding (AMC) scheme in new generation cellular networks. The main purpose of this is to correct the estimated Signal-to-Interference-plus-Noise ratio (SINR) at gNB and select the appropriate Modulation and Coding Scheme (MCS) so the User Equipment (UE) can decode the data successfully. LÄS MER