Nash convergence of mean-based learning algorithms in first price auctions
Understanding the convergence properties of learning dynamics in repeated auctions is a
timely and important question in the area of learning in auctions, with numerous applications …
timely and important question in the area of learning in auctions, with numerous applications …
Payoff-based learning of nash equilibria in merely monotone games
T Tatarenko, M Kamgarpour - IEEE Transactions on Control of …, 2024 - ieeexplore.ieee.org
We address learning Nash equilibria in convex games under the payoff information setting.
We consider the case in which the game pseudo-gradient is monotone but not necessarily …
We consider the case in which the game pseudo-gradient is monotone but not necessarily …
Bandit learning in convex non-strictly monotone games
T Tatarenko, M Kamgarpour - arXiv preprint arXiv:2009.04258, 2020 - arxiv.org
We address learning Nash equilibria in convex games under the payoff information setting.
We consider the case in which the game pseudo-gradient is monotone but not necessarily …
We consider the case in which the game pseudo-gradient is monotone but not necessarily …
Improved learning rates in multi-unit uniform price auctions
Motivated by the strategic participation of electricity producers in electricity day-ahead
market, we study the problem of online learning in repeated multi-unit uniform price auctions …
market, we study the problem of online learning in repeated multi-unit uniform price auctions …
Learning to Bid in Forward Electricity Markets Using a No-Regret Algorithm
AG Abate, D Majdi, J Kazempour… - arXiv preprint arXiv …, 2024 - arxiv.org
It is a common practice in the current literature of electricity markets to use game-theoretic
approaches for strategic price bidding. However, they generally rely on the assumption that …
approaches for strategic price bidding. However, they generally rely on the assumption that …
On the theory and applications of mechanism design and coalitional games in electricity markets
O Karaca - arXiv preprint arXiv:2012.05047, 2020 - arxiv.org
Although the specific structures of electricity markets are diverse around the world, they were
all conceived on the premise of predictable, controllable generation with nonnegligible …
all conceived on the premise of predictable, controllable generation with nonnegligible …
Robust Correlated Equilibrium: Definition and Computation
We study N-player finite games with costs perturbed due to time-varying disturbances in the
underlying system and to that end we propose the concept of Robust Correlated Equilibrium …
underlying system and to that end we propose the concept of Robust Correlated Equilibrium …
Analysis of a Learning Based Algorithm for Budget Pacing
MT Hajiaghayi, M Springer - arXiv preprint arXiv:2205.13330, 2022 - arxiv.org
In this paper, we analyze a natural learning algorithm for uniform pacing of advertising
budgets, equipped to adapt to varying ad sale platform conditions. On the demand side …
budgets, equipped to adapt to varying ad sale platform conditions. On the demand side …
Learning and Efficiency in Multi-Agent Systems
PG Sessa - 2022 - research-collection.ethz.ch
Several important real-world problems involve multiple entities interacting with each other
and can thus be modeled as multi-agent systems. Multi-agent systems are at the core of our …
and can thus be modeled as multi-agent systems. Multi-agent systems are at the core of our …
H∞ interactive controller design for teaching purposes
JM Díaz, S Dormido, B Nicolau, R Costa-Castelló - IFAC-PapersOnLine, 2020 - Elsevier
H∞-based controller design is one of the most powerful methodologies for controller design
in the frequency domain. Unfortunately, its use requires advanced knowledge of control …
in the frequency domain. Unfortunately, its use requires advanced knowledge of control …