Sökning: "random game"

Visar resultat 21 - 25 av 62 uppsatser innehållade orden random game.

1. 21. Interventions for Identifying Context-Specific Causal Structures

   Master-uppsats, KTH/Matematik (Avd.)

   Författare :Georgios-Nikolaos Karelas; [2021]
   Nyckelord :causality; game theory; mathematics; kausalitet; spelteori; matematik;

   Sammanfattning : The problem of causal discovery is to learn the true causal relations among a system of random variables based on the available data. Learning the true causal structure of p variables can sometimes be difficult, but it is crucial in many fields of science, such as biology, sociology and artificial intelligence. LÄS MER

3. 22. En eventstudie om abnormal avkastning på spelsläpp hos svenska spelutvecklarbolag

   Kandidat-uppsats, Södertörns högskola/Företagsekonomi

   Författare :Fredric Axman Lundbom; Edward Nguyen; [2021]
   Nyckelord :game release; event study; game developer companies; effective market hypothesis; Random Walk Hypothesis; accumulated abnormal returns; Spelsläpp; eventstudie; spelutvecklarbolag; effektiva marknadshypotesen; Random Walk Hypothesis; ackumulerad abnormal avkastning.;

   Sammanfattning : This essay examines the impact of game releases on the Swedish stock market. As previous research has examined product launches and news releases, this thesis intends to investigate game releases by game developer companies such as developers of computer, console or mobile games. LÄS MER

4. 23. Clustering and Classification of Time Series in Real-Time Strategy Games - A machine learning approach for mapping StarCraft II games to clusters of game state time series while limited by fog of war

   Kandidat-uppsats, Göteborgs universitet/Institutionen för data- och informationsteknik

   Författare :Olof Enström; Fredrik Hagström; John Segerstedt; Fredrik Viberg; Arvid Wartenberg; David Weber Fors; [2020-10-29]
   Nyckelord :Classification problem; Cluster analysis; Hierarchical clustering; Machine learning; Neural network; Random forest; Real-time strategy; StarCraft II; Time series;

   Sammanfattning : Real-time strategy (RTS) games feature vast action spaces and incomplete information, thus requiring lengthy training times for AI-agents to master them at the level of a human expert. Based on the inherent complexity and the strategical interplay between the players of an RTS game, it is hypothesized that data sets of played games exhibit clustering properties as a result of the actions made by the players. LÄS MER

5. 24. Deep Reinforcement Learning in Cart Pole and Pong

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

   Författare :Dennis Kuurne Uussilta; Viktor Olsson; [2020]
   Nyckelord :Artificial Intelligence; Machine Learning; Rein-forcement Learning; Deep Q-learning Network; CartPole; Pong;

   Sammanfattning : In this project, we aim to reproduce previous resultsachieved with Deep Reinforcement Learning. We present theMarkov Decision Process model as well as the algorithms Q-learning and Deep Q-learning Network (DQN). We implement aDQN agent, first in an environment called CartPole, and later inthe game Pong. LÄS MER

7. 25. Benchmarking and Analysis of Entity Referencing Within Open-Source Entity Component Systems

   Kandidat-uppsats, Malmö universitet/Fakulteten för teknik och samhälle (TS)

   Författare :Hugo Hansen; Oliver Öhrström; [2020]
   Nyckelord :ECS; Entity Component System; C ; Benchmarking; Open Source; Libraries; Data Oriented Design; Object Oriented Design; OOD; DOD; EnTT; EntityX;

   Sammanfattning : Runtime performance is essential for real time games, the faster a game can run the more features designers can put into the game to accomplish their vision.A popular architecture for video games is the Entity Component System architecture aimed to improve both object composition and performance. LÄS MER