TYPES OF MARKOV DECISION PROCESSES, ANTAGONISTIC GAMES, AND MATRIX GAMES: AN ANALYTICAL OVERVIEW
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Keywords: Markov Decision Processes (MDPs), Antagonistic Games, Matrix Games, Nash Equilibrium, Game Theory, Multi-Agent Systems, Reinforcement Learning, Strategic Interactions, Stochastic Games, Payoff Matrix.##article.abstract##
Annotation:This article explores three key decision-making frameworks: Markov Decision Processes (MDPs), Antagonistic Games, and Matrix Games. MDPs model sequential decision-making in uncertain environments, while Antagonistic and Matrix Games analyze competitive scenarios between agents. The study highlights their applications in areas such as AI, robotics, economics, and cybersecurity, emphasizing the interconnections between these models, including game-theoretic MDPs and multi-agent reinforcement learning. The article provides a comprehensive overview of how these frameworks optimize strategies and predict behavior in dynamic systems.
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