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RADDICS SIGNED

Reliable Data-Driven Decision Making in Cyber-Physical Systems

Total Cost €

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EC-Contrib. €

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Partnership

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 RADDICS project word cloud

Explore the words cloud of the RADDICS project. It provides you a very rough idea of what is the project "RADDICS" about.

motivated    rl    strive    abstraction    optimal    breakthroughs    seek    data    active    accurate    energy    policies    pursuing    simulated    explicitly    explored    pursue    perspective    employing    bayesian    assumptions    optimizing    safely    erc    interdisciplinary    reliability    limitations    powerful    robustness    experiments    dangerous    tackle    safe    cyber    guaranteeing    platforms    simulations    optimization    priori    extremely    free    boundary    estimation    provably    dramatic    pushes    robotic    gaussian    physical    theory    episodic    visited    computing    unknown    successes    power    ideas    overcome    extensively    fundamental    electron    rarely    rethink    environments    tuning    photovoltaic    learning    breakthrough    opt    powerplants    specified    closed    exploration    reasoning    near    models    proposition    deep    time    first    dynamics    imitation    bootstrapping    games    cps    initial    bridging    probability    nonparametric    performance    dimensional    laser    unsafe    efficiency    decision    fidelity    regularity    world   

Project "RADDICS" data sheet

The following table provides information about the project.

Coordinator
EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH 

Organization address
address: Raemistrasse 101
city: ZUERICH
postcode: 8092
website: https://www.ethz.ch/de.html

contact info
title: n.a.
name: n.a.
surname: n.a.
function: n.a.
email: n.a.
telephone: n.a.
fax: n.a.

 Coordinator Country Switzerland [CH]
 Total cost 1˙996˙500 €
 EC max contribution 1˙996˙500 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2018-COG
 Funding Scheme ERC-COG
 Starting year 2019
 Duration (year-month-day) from 2019-01-01   to  2023-12-31

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    EIDGENOESSISCHE TECHNISCHE HOCHSCHULE ZUERICH CH (ZUERICH) coordinator 1˙996˙500.00

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 Project objective

This ERC project pushes the boundary of reliable data-driven decision making in cyber-physical systems (CPS), by bridging reinforcement learning (RL), nonparametric estimation and robust optimization. RL is a powerful abstraction of decision making under uncertainty and has witnessed dramatic recent breakthroughs. Most of these successes have been in games such as Go - well specified, closed environments that - given enough computing power - can be extensively simulated and explored. In real-world CPS, however, accurate simulations are rarely available, and exploration in these applications is a highly dangerous proposition.

We strive to rethink Reinforcement Learning from the perspective of reliability and robustness required by real-world applications. We build on our recent breakthrough result on safe Bayesian optimization (SAFE-OPT): The approach allows - for the first time - to identify provably near-optimal policies in episodic RL tasks, while guaranteeing under some regularity assumptions that with high probability no unsafe states are visited - even if the set of safe parameter values is a priori unknown.

While extremely promising, this result has several fundamental limitations, which we seek to overcome in this ERC project. To this end we will (1) go beyond low-dimensional Gaussian process models and towards much richer deep Bayesian models; (2) go beyond episodic tasks, by explicitly reasoning about the dynamics and employing ideas from robust control theory and (3) tackle bootstrapping of safe initial policies by bridging simulations and real-world experiments via multi-fidelity Bayesian optimization, and by pursuing safe active imitation learning.

Our research is motivated by three real-world CPS applications, which we pursue in interdisciplinary collaboration: Safe exploration of and with robotic platforms; tuning the energy efficiency of photovoltaic powerplants and safely optimizing the performance of a Free Electron Laser.

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The information about "RADDICS" are provided by the European Opendata Portal: CORDIS opendata.

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