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We study a class of stochastic dynamic games that exhibit strategic complementarities between players; formally, in the games we consider, the payoff of a player has increasing differences between her own state and the empirical…

Computer Science and Game Theory · Computer Science 2010-12-13 Sachin Adlakha , Ramesh Johari

In this paper, we present an efficient algorithm to solve online Stackelberg games, featuring multiple followers, in a follower-agnostic manner. Unlike previous works, our approach works even when leader has no knowledge about the…

Optimization and Control · Mathematics 2024-03-28 Chinmay Maheshwari , James Cheng , S. Shankar Sasty , Lillian Ratliff , Eric Mazumdar

Differential Dynamic Programming is an optimal control technique often used for trajectory generation. Many variations of this algorithm have been developed in the literature, including algorithms for stochastic dynamics or state and input…

Optimization and Control · Mathematics 2022-05-26 Dennis Gramlich , Carsten W. Scherer , Christian Ebenbauer

Smart metering infrastructure allows for two-way communication and power transfer. Based on this promising technology, we propose a demand-side management (DSM) scheme for a residential neighbourhood of prosumers. Its core is a discrete…

Computer Science and Game Theory · Computer Science 2018-07-24 Matthias Pilz , Luluwah Al-Fagih

We study online reinforcement learning in average-reward stochastic games (SGs). An SG models a two-player zero-sum game in a Markov environment, where state transitions and one-step payoffs are determined simultaneously by a learner and an…

Machine Learning · Computer Science 2017-12-05 Chen-Yu Wei , Yi-Te Hong , Chi-Jen Lu

In this paper, we investigate a new model of a linear-quadratic mean-field stochastic Stackelberg differential game with one leader and two followers, in which the leader is allowed to stop her strategy at a random time. Our overarching…

Optimization and Control · Mathematics 2021-06-08 Zhun Gou , Nan-jing Huang , Ming-hui Wang

The paper presents a new method for approximating Strong Stackelberg Equilibrium in general-sum sequential games with imperfect information and perfect recall. The proposed approach is generic as it does not rely on any specific properties…

Computer Science and Game Theory · Computer Science 2022-08-16 Jan Karwowski , Jacek Mańdziuk

We study a pessimistic stochastic bilevel program in the context of sequential two-player games, where the leader makes a binary here-and-now decision, and the follower responds a continuous wait-and-see decision after observing the…

Optimization and Control · Mathematics 2022-06-09 Akshit Goyal , Yiling Zhang , Chuan He

This paper is devoted to a Stackelberg stochastic differential game for a linear mean-field type stochastic differential system with a mean-field type quadratic cost functional in finite horizon. The coefficients in the state equation and…

Optimization and Control · Mathematics 2023-08-22 Zixuan Li , Jingtao Shi

Two-player mean-payoff Stackelberg games are nonzero-sum infinite duration games played on a bi-weighted graph by Leader (Player 0) and Follower (Player 1). Such games are played sequentially: first, Leader announces her strategy, second,…

Optimization and Control · Mathematics 2021-08-04 Mrudula Balachander , Shibashis Guha , Jean-François Raskin

This paper investigates the motion planning of autonomous dynamical systems modeled by Markov decision processes (MDP) with unknown transition probabilities over continuous state and action spaces. Linear temporal logic (LTL) is used to…

Machine Learning · Computer Science 2022-01-25 Mingyu Cai , Mohammadhosein Hasanbeig , Shaoping Xiao , Alessandro Abate , Zhen Kan

We study stochastic motion planning problems which involve a controlled process, with possibly discontinuous sample paths, visiting certain subsets of the state-space while avoiding others in a sequential fashion. For this purpose, we first…

Optimization and Control · Mathematics 2017-11-27 Peyman Mohajerin Esfahani , Debasish Chatterjee , John Lygeros

Multi-defender Stackelberg Security Games (MSSG) have recently gained increasing attention in the literature. However, the solutions offered to date are highly sensitive, wherein even small perturbations in the attacker's utility or slight…

Computer Science and Game Theory · Computer Science 2024-12-17 Dolev Mutzari , Yonatan Aumann , Sarit Kraus

We consider a dynamic game with asymmetric information where each player observes privately a noisy version of a (hidden) state of the world V, resulting in dependent private observations. We study structured perfect Bayesian equilibria…

Systems and Control · Electrical Eng. & Systems 2020-09-10 Nasimeh Heydaribeni , Achilleas Anastasopoulos

Stochastic and soft optimal policies resulting from entropy-regularized Markov decision processes (ER-MDP) are desirable for exploration and imitation learning applications. Motivated by the fact that such policies are sensitive with…

Machine Learning · Computer Science 2022-01-03 Tien Mai , Patrick Jaillet

The prisoner's dilemma game is the most known contribution of game theory into social sciences. Here we describe new implications of this game for transactional and transformative leadership. While the autocratic (Stackelberg's) leadership…

Physics and Society · Physics 2019-10-22 S. G. Babajanyan , A. V. Melkikh , A. E. Allahverdyan

The Double Linear Policy (DLP) framework guarantees a Robust Positive Expectation (RPE) under optimized constant-weight designs or admissible prespecified time-varying policies. However, the sequential optimization of these time-varying…

Systems and Control · Electrical Eng. & Systems 2026-04-02 Tan Chin Hong , Chung-Han Hsieh

This paper is devoted to a high-dimensional mixed leadership stochastic differential game on a finite horizon in feedback information mode, where the control variables enter into the diffusion term of state equation. A verification theorem…

Optimization and Control · Mathematics 2022-11-28 Qi Huang , Jingtao Shi

This paper investigates the non-zero-sum linear-quadratic stochastic Stackelberg differential games with affine constraints, which depend on both the follower's response and the leader's strategy. With the help of the stochastic Riccati…

Optimization and Control · Mathematics 2024-12-30 Zhun Gou , Nan-Jing Huang , Xian-Jun Long , Jian-Hao Kang

As predictive models are deployed into the real world, they must increasingly contend with strategic behavior. A growing body of work on strategic classification treats this problem as a Stackelberg game: the decision-maker "leads" in the…

Machine Learning · Computer Science 2022-02-01 Tijana Zrnic , Eric Mazumdar , S. Shankar Sastry , Michael I. Jordan