Oracles & followers: Stackelberg equilibria in deep multi-agent reinforcement learning

M Gerstgrasser, DC Parkes - International Conference on …, 2023 - proceedings.mlr.press
Stackelberg equilibria arise naturally in a range of popular learning problems, such as in
security games or indirect mechanism design, and have received increasing attention in the …

Blockchain-empowered resource allocation in Multi-UAV-enabled 5G-RAN: a multi-agent deep reinforcement learning approach

AM Seid, A Erbad, HN Abishu… - IEEE Transactions …, 2023 - ieeexplore.ieee.org
In 5G and B5G networks, real-time and secure resource allocation with the common telecom
infrastructure is challenging. This problem may be more severe when mobile users are …

Coordinating followers to reach better equilibria: End-to-end gradient descent for stackelberg games

K Wang, L Xu, A Perrault, MK Reiter… - Proceedings of the AAAI …, 2022 - ojs.aaai.org
A growing body of work in game theory extends the traditional Stackelberg game to settings
with one leader and multiple followers who play a Nash equilibrium. Standard approaches …

Dynamic pricing optimization for commercial subcontracting power suppliers engaging demand response considering building virtual energy storage

H Huang, Y Ning, Y Jiang, Z Tang, Y Qian… - Frontiers in Energy …, 2024 - frontiersin.org
Commercial buildings have abundant flexible energy resources for demand response (DR).
The electricity price for tenants in the commercial building is generally issued by a …

Navigating in a space of game views

MP Wellman, K Mayo - Autonomous Agents and Multi-Agent Systems, 2024 - Springer
Game-theoretic modeling entails selecting the particular elements of a complex strategic
situation deemed most salient for strategic analysis. Recognizing that any game model is …

The Synergetic Effect in the Management of Active System with Distributed Control

S Chernov, L Chernova, L Chernova… - 2023 IEEE 18th …, 2023 - ieeexplore.ieee.org
The synergetic reasonability of joining the efforts of the centers of competence in the
management of certain object participating in the game has been proved based on a theory …

Integrating Machine Learning and Optimization with Applications in Public Health and Sustainability

K Wang - 2023 - search.proquest.com
The field of artificial intelligence (AI) has garnered increasing attention in the realms of
public health and conservation due to its potential to characterize complex dynamics and …

[图书][B] Learning and Decision-Making in Competitive and Uncertain Systems

T Fiez - 2021 - search.proquest.com
As a result of the demonstrated potential for impact in traditional use cases, progressively
more is being asked of machine learning methods. This evolution has lead to a renewed …

[PDF][PDF] Incentives for Individual Compliance with Pandemic Response Measures

B Pejó, G Biczók - crysys.hu
The current coronavirus pandemic is pushing individuals, businesses and governments to
the limit. Even with the recently emerged hope of rapidly developed vaccines, people still …

A Game-Theoretic Approach for Hierarchical Epidemic Control

F Jia, A Mate, Z Li, S Jabbari, M Chakraborty… - arXiv preprint arXiv …, 2021 - arxiv.org
We design and analyze a multi-level game-theoretic model of hierarchical policy
interventions for epidemic control, such as those in response to the COVID-19 pandemic …