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Eliminating Majority Illusion is Easy

https://arxiv.org/html/2407.20187v1
1 Introduction 1.1 The Illusion Elimination Problem 1.2 Our Contributions. 1.3 Related Work. 2 Preliminaries 3 Majority Illusion Addition Elimination (MIAE) 3.1 A First Attempt 3.2 A Second Attempt 3.3 A TDI System 3.4 A Polynomial Time

Maximizing utility in multi-agent environments by anticipating the

https://arxiv.org/html/2407.04889v1
behavior of other learners 1 Introduction Setting. Zero-sum games. General-sum games. 1.1 Preliminaries 1.2 Algorithms for the learner 1.3 Our results 1.3.1 Zero sum games Continuous-time games. Discrete-time games. 1.3.2 A lower bound

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https://arxiv.org/pdf/1811.12628
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Stochastic Games with Minimally Bounded Action Costs

https://arxiv.org/html/2407.18010v2
1 Introduction 2 Formulation 3 Existence of a Value and Saddle Point Equilibrium 4 Learning in Unknown Environments 4.1 Convergence using Linear Function Approximators 5 Intervention Budget Constraints 6 Discussion on Subcases 7 Related

Homogeneous Distributed Observers for Quasilinear Systems

https://arxiv.org/html/2407.05763v1
1 Introduction 2 Preliminaries 2.1 Graph Theory 2.2 Generalized Homogeneity 3 Problem Statement 4 Basic Idea of the Observer Design 5 Homogeneous Observer Design 5.1 Globally Homogeneous Distributed Observer 5.2 Locally Homogeneous