Global ETD Search
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Showing 1 to 9 of 9 for “"Extensive Form Games"”.
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Multiagent Approaches to Enhance Learning and Trust in AI Systems
… interacting under uncertainty and limited information. To be effective, agents must adapt continuously while operating efficiently in large and complex decision spaces. Using frameworks such as extensive form games and multiagent reinforcement learning, this work demonstrates how regret …
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Essays on Economic Decision Making
… 2 studies an individual's decision making in extensive-form games under ambiguity when the individual is ambiguous about an opponent's moves. In this chapter, a player follows Choquet Expected Utility preferences, since the standard Expected Utility cannot explain the situations of ambiguity. …
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Reasoning and decisions in partially observable games
The extensive form game is a formalism used to model environments where agents make sequences of decisions, possibly in the face of uncertainty about the state of the world and the decisions made by other agents. Such games can be expressed in the form of a tree. Game-theoretic solutions to …
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On Solving Larger Games: Designing New Algorithms Adaptable to Deep Reinforcement Learning
… design of algorithms capable of handling large games where the state space is too large to store strategies in a tabular format from a theoretical perspective. Specifically, we focus on developing algorithms suitable for deep reinforcement learning in two-player zero-sum extensive-form games. …
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Efficient Learning and Computation of Linear Correlated Equilibrium in General Convex Games
… coarse correlated equilibria—in general convex games. These are games where the number of pure strategies is potentially exponential in the natural representation of the game, such as extensive-form games. Our work identifies linear correlated equilibria as the tightest known notion of …
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Dealing With Misbehavior In Distributed Systems: A Game-Theoretic Approach
… sealed bid auction. We also build models using extensive form games to analyze the interactions of the attackers and the defender in a security game involving honeypots.</p> <p>Multicast cost sharing is an important problem and very few distributed strategyproof mechanisms exist to calculate the …
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Exact Solution of Bayes and Minimax Change-Detection Problems
… Bayes or minimax based on the availability of information on the change-time distribution. A Bayes optimal solution uses prior information about the distribution of the change time to minimize the expected cost, whereas a minimax optimal solution minimizes the cost under the worst-case …
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Near-Optimal Learning in Sequential Games
… decision making problems become sequential games. In this setting, the learning objective shifts from finding an optimal decision rule to finding a Nash equilibrium, where none of the agents can increase their reward by unilaterally switching to another decision rule. To handle both the …
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Theoretical Foundations for Learning in Games and Dynamic Environments
… to do as a function of the environment’s state. Extensive work spanning multiple domains such as economics, computer science, and statistics has been developed to model these decision-making problems. This has led to many celebrated results, which include, for instance, a considerable body of …