Publications associées à Optimal Combination Policies For Adaptive Social Learning

Frihet, sikkerhet, forstaden: Brev fra Amerika

Why have countries formerly leading public policies of housing – Norway, the U.K., France, etc. – shifted towards privatizing accommodation from the late 1970s? Have these States merely let go of housing and handed it over to private interests in the name ...

2024

Diffusion of connected and autonomous vehicles concerning mode choice, policy interventions and sustainability impacts: A system dynamics modelling study

Evangelos Paschalidis

Connected and autonomous vehicles (CAV) have seen a rapid development over the past decade. However, wide diffusion of high level CAVs is still decades to come, and will depend on many technological, policy and public acceptance factors. Merging a traditio ...

ELSEVIER SCI LTD2023

Endogenous Energy Efficiency Improvement in Housing and Cement Sectors in Switzerland

Sergey Arzoyan

The reduction of energy consumption in the residential building stock and cement industry is a substantial component of the Swiss Energy Strategy 2050. Therefore, it is vital to identify the potential for EEI in these two sectors. In this study, a new meth ...

EPFL2023

Predicting party switching through machine learning and open data

Silvestro Micera, Emanuele Rossi

Parliament dynamics might seem erratic at times. Predicting future voting patterns could support policy design based on the simulation of voting scenarios. The availability of open data on legislative activities and machine learning tools might enable such ...

CELL PRESS2023

Environmental policies: designing acceptable road pricing and voluntary waste sorting schemes

Linda Melina Tesauro

Growing urban population implies many challenges for the municipalities in terms of mobility, housing, waste management or infrastructures. Public policies are thus needed to ensure a sustainable development. The main objective of this thesis is to analyze ...

EPFL2022

The Economics of Incomplete Plan - on Conditions, Procedures and Design of Future Mission - Oriented Innovation Policies

Dominique Foray

The buzzword in industrial policy and innovation policy circles is mission-oriented innovation policy (MOIP) -which means a policy to encourage innovation intended to accomplish a certain missionwhether it be a societal challenge (climate change, global he ...

INST ESTUDIOS FISCALES2022

Optimal recovery of unsecured debt via interpretable reinforcement learning

Thomas Alois Weber, Michael Mark, Huanxi Liu

This paper addresses the issue of interpretability and auditability of reinforcement-learning agents employed in the recovery of unsecured consumer debt. To this end, we develop a deterministic policy-gradient method that allows for a natural integration o ...

2022

From Marshall Plan to “Hilton in the wild”: The Transnational History of a Cooperative Housing Block in Esat, Ankara

Sila Karatas

This paper concerns the planning, design, and construction history of a postwar multifamily housing block in Ankara, Turkey, viewed from the perspective of the transnational and local networks behind its realization. Built by the Mintrak Building Cooperati ...

2022

The Rebound Effects from Industrial Energy Efficiency Improvements

Michel Zimmermann

In energy policy, energy efficiency constitutes a central element in reducing domestic and, specifically, industrial en-ergy use. Unfortunately, the effectiveness of energy efficiency improvements in achieving its targets is known to be limited by rebound ...

EPFL2022

Multiagent Fully Decentralized Value Function Learning With Linear Convergence Rates

Ali H. Sayed, Kun Yuan, Lucas Cesar Eduardo Cassano

This article develops a fully decentralized multiagent algorithm for policy evaluation. The proposed scheme can be applied to two distinct scenarios. In the first scenario, a collection of agents have distinct datasets gathered by following different behav ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Logical Team Q-learning: An approach towards factored policies in cooperative MARL

Ali H. Sayed, Lucas Cesar Eduardo Cassano

We address the challenge of learning factored policies in cooperative MARL scenarios. In particular, we consider the situation in which a team of agents collaborates to optimize a common cost. The goal is to obtain factored policies that determine the indi ...

MICROTOME PUBLISHING2021

Exploring policy change through agent-based simulation

Raphaël Klein

Policymaking is a complex process that has been studied using policy process theories almost exclusively. These theories have been built using a large number of qualitative cases. Such methods are useful for theory building but remain limited for theory ex ...

EPFL2021

Gramian-Based Adaptive Combination Policies For Diffusion Learning Over Networks

Ali H. Sayed, Stefan Vlaski, Yigit Efe Erginbas

This paper presents an adaptive combination strategy for distributed learning over diffusion networks. Since learning relies on the collaborative processing of the stochastic information at the dispersed agents, the overall performance can be improved by d ...

IEEE2021

Optimal Adversarial Policies in the Multiplicative Learning System With a Malicious Expert

Seyed Jalal Etesami, Negar Kiyavash

We consider a learning system based on the conventional multiplicative weight ( MW) rule that combines experts' advice to predict a sequence of true outcomes. It is assumed that one of the experts is malicious and aims to impose the maximum loss on the sys ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

What determines the attitude-behavior link when voting on renewable energy policies? The roles of problem perception and policy design

Philippe Thalmann

This chapter sheds light on the paradox between the general perception of climate change related problems and resistance to measures addressing it, namely the support of renewable energy policies at the ballot box. Using conjoint analyses, we investigate t ...

Edward Elgar Publishing2021

Adaptive Social Learning

Ali H. Sayed, Virginia Bordignon

This work proposes a novel strategy for social learning by introducing the critical feature of adaptation. In social learning, several distributed agents update continually their belief about a phenomenon of interest through: i) direct observation of strea ...

IEEE-INST ELECTRICAL ELECTRONICS ENGINEERS INC2021

Surprise-based model estimation in reinforcement learning: algorithms and brain signatures

Vasiliki Liakoni

Learning how to act and adapting to unexpected changes are remarkable capabilities of humans and other animals. In the absence of a direct recipe to follow in life, behaviour is often guided by rewarding and by surprising events. A positive or a negative o ...

EPFL2021

A review of approaches to low-carbon transition of high-rise residential buildings in China

Jean-Louis Scartezzini, Dasaraden Mauree, Yi Wang

In developing countries with a large population and fast urbanization, High-rise Residential Buildings (HRBs) have unavoidably become a very common, if not the most, accommodation solution. The paradigm of HRB energy consumption is characterized by high-de ...

PERGAMON-ELSEVIER SCIENCE LTD2020

The organisation of science: topics, incentives and funding

Omar Ballester Gonzalez

Ever since the links between the development of new technologies and economic growth became evident, researchers have attempted to study how the creation of knowledge fosters progress. If pushing the frontier of knowledge has an impact on progress and well ...

EPFL2020

Prepare Scientists to Engage in Science‐Policy

Julia Schmale

There is a dire need for deeper science‐policy engagement to face recent developments such as entering into the Anthropocene and our dependence as a species on technological and scientific advancements. However, there is a lack of preparedness and training ...

2020