Sökning: "Multi-agent Player"
Visar resultat 1 - 5 av 15 uppsatser innehållade orden Multi-agent Player.
1. Enhancing video game experience with playtime training and tailoring of virtual opponents : Using Deep Q-Network based Reinforcement Learning on a Multi-Agent Environment
Master-uppsats,Sammanfattning : When interacting with fictional environments, the users' sense of immersion can be broken when characters act in mechanical and predictable ways. The vast majority of AIs for such fictional characters, that control their actions, are statically scripted, and expert players can learn strategies that take advantage of this to easily win challenges that were intended to be hard. LÄS MER
2. Multi-Agent Information Gathering Using Stackelberg Games
Master-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Multi-agent information gathering (MA-IG) enables autonomous robots to cooperatively collect information in an unfamiliar area. In some scenarios, the focus is on gathering the true mapping of a physical quantity such as temperature or magnetic field. LÄS MER
3. Learning Multi-Agent Combat Scenarios in StarCraft II with League Training : an exploration of advanced learning techniques on a smaller scale
Master-uppsats, Linköpings universitet/Artificiell intelligens och integrerade datorsystemSammanfattning : Google DeepMind trained their state-of-the-art StarCraft II agent AlphaStar using leaguetraining with massive computational power. In this thesis we explore league training onsmall-scale combat scenarios in StarCraft II, using limited computational resources, to an-swer whether this approach is suitable for smaller problems. LÄS MER
4. Undersökning av stabilisering och icke-stabilisering av MKBSC i fleragentsspel
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : There are constructions called KBSC and MKBSC. KBSC is used to expand a player’s knowledge of the conditions in a game graph, while MKBSC works the same but for game graphs with at least two players working together towards a common goal. LÄS MER
5. Investigating the impact of agent observations on stabilization of the iterated Multiplayer Knowledge Based Subset Construction
Kandidat-uppsats, KTH/Skolan för elektroteknik och datavetenskap (EECS)Sammanfattning : Multi-agent games and strategy synthesis within them is of great interest to several applications, for example robotics and manufacturing. The Multiplayer Knowledge Based Subset Construction (MKBSC) could be a useful tool for such strategy synthesis. LÄS MER
