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Beyond Time-Average Convergence: Near-Optimal Uncoupled Online Learning via Clairvoyant Multiplicative Weights Update

Efstratios Panteleimon Skoulakis

In this paper we provide a novel and simple algorithm, Clairvoyant Multiplicative Weights Updates (CMWU), for convergence to \textit{Coarse Correlated Equilibria} (CCE) in general games. CMWU effectively corresponds to the standard MWU algorithm but where ...

2022

A systemic framework to categorize Circular Economy interventions: An application to the construction and demolition sector

Claudia Rebeca Binder Signer, Valeria Superti, Cynthia Houmani

The Circular Economy (CE) concept has recently gained momentum as a perspective to tackle global challenges such as resource scarcity and waste management. Multiple types of interventions have been proposed to support the transition towards a CE. This pape ...

2021

The diversity of moral preferences: Evolutionary foundations and some implications in environmental economics

Boris Thurm

Empirical evidence suggests that there exists substantial heterogeneity in individuals' social preferences. However, there is little theoretical basis supporting this observation and economic models often assume that all individuals are identical. Hence, t ...

EPFL2019

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

Partial Truthfulness in Minimal Peer Prediction Mechanisms with Limited Knowledge

Boi Faltings, Goran Radanovic

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

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

Selection methods regulate evolution of cooperation in digital evolution

Dario Floreano, Laurent Keller, Pawel Lichocki

A key, yet often neglected, component of digital evolution and evolutionary models is the 'selection method' which assigns fitness (number of offspring) to individuals based on their performance scores (efficiency in performing tasks). Here, we study with ...

Royal Soc2014

Multi-Agent Learning for Resource Allocation Problems

Ludek Cigler

We analyze resource allocation problems where N independent agents want to access C resources. Each resource can be only accessed by one agent at a time. In order to use the resources efficiently, the agents need to coordinate their access. We focus on dec ...

EPFL2013

Symmetric subgame perfect equilibria in resource allocation