Sökning: "zero-sum games"

Visar resultat 1 - 5 av 8 uppsatser innehållade orden zero-sum games.

1. 1. Hanterande (slängande) av returer inom klädindustrin

   Kandidat-uppsats, Lunds universitet/Företagsekonomiska institutionen

   Författare :Adam Bengtsson; Lisa Holm; Jessika Pham; [2023]
   Nyckelord :Returbeteende; returpolicys; hållbarhet; CSR; produktförstöring; retur Return behavior; return policies; sustainability; product destruction; return; Business and Economics;

   Sammanfattning : Syfte Undersöka konsumenters köp- och returbeteenden vad gäller kläder vid införandet av striktare returpolicys. Teoretiska perspektiv Returbeteende, Categories of online returning behavior, Returpolicy, CSR, Carroll’s Pyramid of Corporate Social Responsibility, Tidigare forskning, Grandiositet och nollsummespel Metod Uppsatsen utgår från en kvantitativ undersökningsmetod och deduktiv ansats. LÄS MER

3. 2. Evaluating the performance of a team consisting of an advanced agent and a less advanced agent in the game Manille : A comparison of agents trained using the CFR algorithm with and without abstractions.

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

   Författare :Oliver Lindgren; Leonardo Rezza; [2023]
   Nyckelord :;

   Sammanfattning : Making artificial intelligence (AI) algorithms solve games has always been an interesting benchmark of AI research. Perfect information games like Chess can be played on a level beyond human capabilities. LÄS MER

4. 3. Self-Play Reinforcement Learning for Finding Intrusion Prevention Strategies

   Master-uppsats, KTH/Matematisk statistik

   Författare :Jakob Stymne; [2022]
   Nyckelord :Network security; automation; reinforcement learning; Markov Security Games; Neural Fictitious Self Play; Nätverkssäkerhet; automatisering; förstärkningsinlärning; Markovianska säkerhetsspel; Neural Fictitious Self Play;

   Sammanfattning : This Master thesis studies automated intrusion prevention using self-play reinforcement learning. We extend a decision-theoretic model of the intrusion prevention use case based on optimal stopping theory proposed in previous work to a game-theoretic setting. LÄS MER

5. 4. Deep Reinforcement LearningA case study of AlphaZero

   Kandidat-uppsats, Uppsala universitet/Institutionen för informationsteknologi

   Författare :Fredrik Mattisson; [2021]
   Nyckelord :;

   Sammanfattning : Using deep neural networks for reinforcement learning has proven very successful, as demonstrated by the AlphaZero algorithm developed by DeepMind in 2018. This algorithm is capable of mastering two-player zero-sum board games entirely by playing against itself. LÄS MER

7. 5. Deep Distributional Temporal Difference Learning for Game Playing

   Master-uppsats, Lunds universitet/Matematisk statistik

   Författare :Frej Berglind; [2019]
   Nyckelord :Reinforcement Learning; Deep Learning; Temporal Difference Learning; Distributional Learning; Game Playing; 5-in-a-row; Artificial Intelligence.; Mathematics and Statistics;

   Sammanfattning : Temporal difference learning is considered one of the most successful methods in reinforcement learning. Recent developments in deep learning have opened up a new world of opportunities. LÄS MER