Sökning: "datavetenskap umu"
Visar resultat 1 - 5 av 467 uppsatser innehållade orden datavetenskap umu.
1. Evaluation of communication protocol performance for use in reinforcement learning training in simulation
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : Since artificial intelligence (AI) is growing more prominent it is interesting to look at the methods used to train AI. One such method is reinforcement learning in simulation, where AI can train safely in the confines of a simulation. LÄS MER
2. An evaluation of Language Integrated Queries (LINQ)
Kandidat-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : Accessing data in databases is an everyday operation that has to function with high performance. The use of Structured Query Language has for a long time been the default way of retrieving and modifying data. Another common approach is through the use of an Object-Relational Mapper. LÄS MER
3. Language Theoretic Properties of Graph Extension Languages : An Investigation of Graph Extension Grammars with Context Matching and Logic
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : Graph extension grammars provide a way to define graph languages. They consist of a regular tree grammar and an algebra. The regular tree grammar generates trees, so-called derivation trees. Those are evaluated by the algebra into a set of graphs. LÄS MER
4. A Comparison of CI/CD Tools on Kubernetes
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : Kubernetes is a fast emerging technological platform for developing and operating modern IT applications. The capacity to deploy new apps and change old ones at a faster rate with less chance of error is one of the key value proposition of the Kubernetes platform. LÄS MER
5. Embracing AWKWARD! A Hybrid Architecture for Adjustable Socially-Aware Agents
Master-uppsats, Umeå universitet/Institutionen för datavetenskapSammanfattning : 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
