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20212026
most citedProbabilistic design of optimal sequential decision-making algorithms in learning and control

15 citations · 24 across the 10 of their papers we have counts for

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7 papers · 1 filter

math.OC2024

Free-Gate: Planning, Control And Policy Composition via Free Energy Gating

Francesca Rossi, Émiland Garrabé, Giovanni Russo

We consider the problem of optimally composing a set of primitives to tackle planning and control tasks. To address this problem, we introduce a free energy computational model for…

math.OC2023

On Convex Data-Driven Inverse Optimal Control for Nonlinear, Non-stationary and Stochastic Systems

Emiland Garrabe, Hozefa Jesawada, Carmen Del Vecchio +1

This paper is concerned with a finite-horizon inverse control problem, which has the goal of reconstructing, from observations, the possibly non-convex and non-stationary cost driv…

math.OC2023★ 1 cited

On a Probabilistic Approach for Inverse Data-Driven Optimal Control

Émiland Garrabé, Hozefa Jesawada, Carmen Del Vecchio +1

We consider the problem of estimating the possibly non-convex cost of an agent by observing its interactions with a nonlinear, non-stationary and stochastic environment. For this i…

math.OC2023

Optimal Decision-Making for Autonomous Agents via Data Composition

Emiland Garrabe, Martina Lamberti, Giovanni Russo

We consider the problem of designing agents able to compute optimal decisions by composing data from multiple sources to tackle tasks involving: (i) tracking a desired behavior whi…

math.OC2022

CRAWLING: a Crowdsourcing Algorithm on Wheels for Smart Parking

Émiland Garrabé, Giovanni Russo

We present the principled design of CRAWLING: a CRowdsourcing Algorirthm on WheeLs for smart parkING. CRAWLING is an in-car service for the routing of connected cars. Specifically,…

math.OC2022★ 15 cited

Probabilistic design of optimal sequential decision-making algorithms in learning and control

Emiland Garrabe, Giovanni Russo

This survey is focused on certain sequential decision-making problems that involve optimizing over probability functions. We discuss the relevance of these problems for learning an…

math.OC2021★ 8 cited

On the design of autonomous agents from multiple data sources

Émiland Garrabé, Giovanni Russo

This paper is concerned with the problem of designing agents able to dynamically select information from multiple data sources in order to tackle tasks that involve tracking a targ…