On the role of trust types and levels on inventory replenishment decision

Publications associées (29)

Page 3 sur 3

À propos
Confidentialité
Mentions légales

Graph Chatbot

Wasserstein Distributionally Robust Learning

Soroosh Shafieezadeh Abadeh

Many decision problems in science, engineering, and economics are affected by uncertainty, which is typically modeled by a random variable governed by an unknown probability distribution. For many practical applications, the probability distribution is onl ...

EPFL2020

Neural Correlates of Reinforcement Learning: eligibility trace, reward prediction error, novelty and surprise

He Xu

In reinforcement learning (RL), an agent makes sequential decisions to maximise the reward it can obtain from an environment. During learning, the actual and expected outcomes are compared to tell whether a decision was good or bad. The difference between ...

EPFL2020

Toward Robust Sensing for Autonomous Vehicles: An Adversarial Perspective

Pascal Frossard, Andrea Cavallaro, Apostolos Modas

Autonomous vehicles (AVs) rely on accurate and robust sensor observations for safety-critical decision making in a variety of conditions. The fundamental building blocks of such systems are sensors and classifiers that process ultrasound, radar, GPS, lidar ...

2020

Frictional Intermediation in Over-the-Counter Markets

Julien Hugonnier

We extend Duffie et al.'s (2005) search-theoretic model of over-the-counter (OTC) asset markets, allowing for a decentralized inter-dealer market with arbitrary heterogeneity in dealers' valuations (or, equivalently, inventory costs). We develop a solution ...

OXFORD UNIV PRESS2020

JIT works: decide when all data is known (VLDB Women in Database Research Award talk)

Anastasia Ailamaki

When the time comes to make a critical decision, it is of paramount importance to prepare enough so that all the information necessary is available at decision time. Under-preparation leads to uninformed decisions; over-preparation, however, may lead to co ...

ASSOC COMPUTING MACHINERY2020

One-shot learning and behavioral eligibility traces in sequential decision making

Michael Herzog, Wulfram Gerstner, Marco Philipp Lehmann, Kerstin Preuschoff, He Xu, Vasiliki Liakoni

In many daily tasks, we make multiple decisions before reaching a goal. In order to learn such sequences of decisions, a mechanism to link earlier actions to later reward is necessary. Reinforcement learning (RL) theory suggests two classes of algorithms s ...

2019

The Decision Rule Approach to Optimisation under Uncertainty: Methodology and Applications

Daniel Kuhn, Wolfram Wiesemann

Dynamic decision-making under uncertainty has a long and distinguished history in operations research. Due to the curse of dimensionality, solution schemes that naively partition or discretize the support of the random problem parameters are limited to sma ...

2019

Pessimistic outcome expectancy does not explain ambiguity aversion in decision-making under uncertainty

Martin Alois Rohrmeier

When faced with a decision, most people like to know the odds and prefer to avoid ambiguity. It has been suggested that this aversion to ambiguity is linked to people's assumption of worst possible outcomes. We used two closely linked behavioural tasks in ...

Nature Research2019

A holistic decision making framework for a vehicle sharing system

Michel Bierlaire, Nikola Obrenovic, Selin Ataç

The vehicle sharing systems (VSSs) are becoming more and more popular due to both financial and environmental effects. On the other hand, they face many challenges, such as inventory management of the vehicles and parking spots, imbalance of the vehicles, ...

2019

Page 3 sur 3