Concept

Prisoner's dilemma

Related publications (38)

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Bridging Bayesian and Minimax Mean Square Error Estimation via Wasserstein Distributionally Robust Optimization

Daniel Kuhn, Viet Anh Nguyen, Soroosh Shafieezadeh Abadeh, Peyman Mohajerin Esfahani

We introduce a distributionally robust minimium mean square error estimation model with a Wasserstein ambiguity set to recover an unknown signal from a noisy observation. The proposed model can be viewed as a zero-sum game between a statistician choosing a ...

2019

On Risk Reduction in Kelly Betting Using the Conservative Expected Value

Daniel Kuhn, Napat Rujeerapaiboon

The celebrated Kelly betting strategy guarantees, with probability one, higher long-run wealth than any other causal investment strategy. However, on the way to its long-term supremacy, this strategy has a notable downfall: it typically displays high varia ...

2018

A rational decentralized generalized Nash equilibrium seeking for energy markets

Matteo Salani, Lorenzo Nespoli, Vasco Medici

We propose a method to design a decentralized energy market which guarantees individual rationality (IR) in expectation, in the presence of system-level grid constraints. We formulate the market as a welfare maximization problem subject to IR constraints, ...

IEEE2018

We study minimal single-task peer prediction mechanisms that have limited knowledge about agents' beliefs. Without knowing what agents' beliefs are or eliciting additional information, it is not possible to design a truthful mechanism in a Bayesian-Nash se ...

ASSOC ADVANCEMENT ARTIFICIAL INTELLIGENCE2018

Expressing Motivations By Facilitating Other’s Inverse Reinforcement Learning

Pierre Dillenbourg, Wafa Monia Benkaouar Johal, Alexis David Jacq, Ana Paiva

It is often necessary to understand each other’s motivations in order to cooperate. Reaching such a mutual understanding requires two abilities: to build models of other’s motivations in order to understand them, and to build a model of “my” motivations pe ...

Instituto Superiro Technico2017

This paper examines a stochastic formulation of the generalized Nash equilibrium problem where agents are subject to randomness in the environment of unknown statistical distribution. We focus on fully distributed online learning by agents and employ penal ...

IEEE2017

Adaptive learning for stochastic generalized Nash equilibrium problems

Ali H. Sayed

This work examines a stochastic formulation of the generalized Nash equilibrium problem (GNEP) where agents are subject to randomness in the environment of unknown statistical distribution. Three stochastic gradient strategies are developed by relying on a ...

IEEE2016

Process systems engineering studies for the synthesis of catalytic biomass-to-fuels strategies

Jeremy Luterbacher

The goal of this paper is to show how chemical process synthesis and analysis studies can be coupled with experimental heterogeneous catalysis studies to identify promising research directions for the development of strategies for the production of renewab ...

Elsevier2015

A source produces i.i.d. vector samples from a Gaussian distribution, but the user is interested in only one component. In the cache phase, not knowing which component the user is interested in, a first compressed description is produced. Upon learning the ...

2015

Symmetric Subgame-Perfect Equilibria in Resource Allocation

Boi Faltings, Ludek Cigler

We analyze symmetric protocols to rationally coordinate on an asymmetric, efficient allocation in an infinitely repeated N-agent, C-resource allocation problems, where the resources are all homogeneous. Bhaskar proposed one way to achieve this in 2-agent, ...

AI Access Foundation2014