Results 61 to 70 of about 2,400 (182)

Gradient Methods for Solving Stackelberg Games [PDF]

, 2019
Stackelberg Games are gaining importance in the last years due to the raise of Adversarial Machine Learning (AML). Within this context, a new paradigm must be faced: in classical game theory, inter- vening agents were humans whose decisions are generally discrete and low dimensional.
Roi Naveiro, David Ríos Insua
openaire   +6 more sources

Equilibrium Reward for Liquidity Providers in Automated Market Makers

Mathematical Finance, EarlyView.
ABSTRACT We find the equilibrium contract that an automated market maker (AMM) offers to their strategic liquidity providers (LPs) in order to maximize the order flow that gets processed by the venue. Our model is formulated as a leader–follower stochastic game, where the venue is the leader and a representative LP is the follower.
Alif Aqsha, Philippe Bergault, Leandro Sánchez‐Betancourt   +2 more
wiley   +1 more source

Sequential decomposition of Stochastic Stackelberg games

2022 American Control Conference (ACC), 2022
In this paper, we consider a discrete-time stochastic Stackelberg game with a single leader and multiple followers. Both the followers and the leader together have conditionally independent private types, conditioned on action and previous state, that evolve as controlled Markov processes.
openaire   +2 more sources

An Existence Result for Hierarchical Stackelberg v/s Stackelberg Games [PDF]

IEEE Transactions on Automatic Control, 2015
This submission contains some results drawn from an earlier manuscript (http://arxiv.org/abs/1206.2968v2) which was rejected. The earlier manuscript has been split into 3 parts. One part is published in the Proc IEEE CDC, 2013, another is under review with Set-valued and Varitional Analysis (on arxiv).
Ankur A. Kulkarni, Uday V. Shanbhag
openaire   +3 more sources

Personalized Model‐Driven Interventions for Decisions From Experience

Topics in Cognitive Science, EarlyView.
Abstract Cognitive models that represent individuals provide many benefits for understanding the full range of human behavior. One way in which individual differences emerge is through differences in knowledge. In dynamic situations, where decisions are made from experience, models built upon a theory of experiential choice (instance‐based learning ...
Edward A. Cranford, Christian Lebiere, Cleotilde Gonzalez, Palvi Aggarwal, Sterling Somers, Konstantinos Mitsopoulos, Milind Tambe   +6 more
wiley   +1 more source

Learning in Stackelberg Markov Games

CoRR
Designing socially optimal policies in multi-agent environments is a fundamental challenge in both economics and artificial intelligence. This paper studies a general framework for learning Stackelberg equilibria in dynamic and uncertain environments, where a single leader interacts with a population of adaptive followers.
Jun He, Andrew L. Liu, Yihsu Chen
openaire   +2 more sources

Energy Sharing and Coordination Strategies in Multimicrogrid and Electric Vehicle Integration: A Bilevel Game-Theoretic Approach

International Transactions on Electrical Energy Systems
The proliferation of microgrids and the rapid electrification of transportation have intensified competition for distribution-level resources, highlighting the need for effective coordination strategies for energy sharing and electric vehicle (EV ...
Jieyun Zheng, Xin Wei, Shiwei Xie, Zhanghuang Zhang, Jingwei Xue, Ruochen Chen   +5 more
doaj   +1 more source

Collaborative platooning and routing for mixed fleets of electric automated vehicles and conventional trucks

International Transactions in Operational Research, Volume 34, Issue 1, Page 460-500, January 2027.
Abstract The application of automated ground vehicles (AGVs) is well‐established in closed environments such as port terminals, while their operation in open areas remains challenging. In this work, we set out to overcome this limitation by introducing platooning as a transfer mode in heterogeneous vehicle networks.
Nadia Pourmohammad‐Zia, Rudy R. Negenborn, Frederik Schulte   +2 more
wiley   +1 more source

Network scheduling algorithm based on Stackelberg Game with incentive strategy

Tongxin xuebao, 2009
First, a Stackelberg Game network model was built. In this model, the existence of Nash equilibrium was analyzed and the team optimal solution of the network was available.
WEI Jiao-long, HU Jin, DAI Wen-juan, ZOU Jia-hong   +3 more
doaj   +2 more sources

Game Theoretic Approaches for Cooperative Spectrum Sensing in Energy-Harvesting Cognitive Radio Networks

IEEE Access, 2018
In this paper, we propose game-theoretic approaches to model the cooperative spectrum sensing in cognitive radio environment with cognitive secondary users (SU) capable of energy harvesting. An evolutionary game model is considered in the first scenario,
Osama Elnahas, Maha Elsabrouty, Osamu Muta, Hiroshi Furukawa   +3 more
doaj   +1 more source