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BRISC SIGNED

Bounded Rationality in Sensorimotor Coordination

Total Cost €

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EC-Contrib. €

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Partnership

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 Outcomes and results

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 BRISC project word cloud

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

abstraction    motor    intractable    fundamental    football    disaster    learning    bayes    framework    emergence    answering    deviate    power    simultaneously    understand    computational    biological    formed    flexible    capacity    question    themselves    multiple    symbolic    theoretical    missing    experimental    structures    optimal    predictions    humans    performance    intelligent    uncertain    rational    actor    resource    bounded    abstract    outperformed    perceptual    degrees    machines    gathering    models    stream    time    sensorimotor    gold    despite    brisc    actors    decisive    laboratory    drives    speed    navigating    single    link    principles    hierarchical    autonomously    playing    explains    limited    ignore    technological    behavior    potentially    successes    human    takes    individual    zone    allocation    standard    scales    world    optimum    search    effort    drawing    mathematical    environments    blatantly    organize   

Project "BRISC" data sheet

The following table provides information about the project.

Coordinator		 UNIVERSITAET ULM 

Organization address
address: HELMHOLTZSTRASSE 16
city: ULM
postcode: 89081
website: www.uni-ulm.de

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 Germany [DE]
 Project website https://www.uni-ulm.de/in/neuroinformatik/forschung/schwerpunkte/brisc/
 Total cost 1˙434˙250 €
 EC max contribution 1˙434˙250 € (100%)
 Programme 1. H2020-EU.1.1. (EXCELLENT SCIENCE - European Research Council (ERC))
 Code Call ERC-2015-STG
 Funding Scheme ERC-STG
 Starting year 2016
 Duration (year-month-day) from 2016-10-01   to  2021-09-30

 Partnership

Take a look of project's partnership.

# participants  country  role  EC contrib. [€] 
1    UNIVERSITAET ULM DE (ULM) coordinator 1˙434˙250.00
2    LUDWIG-MAXIMILIANS-UNIVERSITAET MUENCHEN DE (MUENCHEN) participant 0.00

Map

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Leaflet | Map data © OpenStreetMap contributors, CC-BY-SA, Imagery © Mapbox

 Project objective

Despite their many successes and great computational power and speed, why are machines still so blatantly outperformed by humans in uncertain environments that require flexible sensorimotor behavior like playing football or navigating a disaster zone? Answering this question requires understanding the mathematical principles of biological sensorimotor control and learning. Over the recent years Bayes-optimal actor models have widely become the gold standard in the mathematical understanding of sensorimotor processing in well-controlled laboratory tasks. However, these models quickly become intractable for real-world problems because they ignore the computational effort required to search for the Bayes-optimum. What is therefore needed is a framework of sensorimotor processing that takes the limited information-processing capacity of bounded rational actors into account and that explains their robust real-world performance. It is the aim of BRISC to establish such a framework by drawing out theoretical predictions and gathering experimental evidence in human motor control, in particular to understand (i) how single bounded rational actors deviate from Bayes-optimal behavior in motor tasks, (ii) how multiple bounded rational actors organize themselves to solve motor tasks that no individual can solve by themselves and (iii) how this drives the emergence of hierarchical control structures that simultaneously process multiple degrees of abstraction at different time scales. Understanding how abstract concepts are formed autonomously from the sensorimotor stream based on resource allocation principles will establish an essential missing link between high-level symbolic and low-level perceptual processing. These advances will provide a decisive step towards a framework for robust and flexible sensorimotor processing, which is not only essential for understanding the fundamental principles of intelligent behavior, but it is also of potentially great technological value.

 Publications

year authors and title journal last update
List of publications.
2019 Heinke Hihn, Sebastian Gottwald, Daniel Braun
An Information-Theoretic On-Line Learning Principle for Specialization in Hierarchical Decision-Making Systems
published pages: , ISSN: , DOI: 		2019 IEEE 58th Conference on Decision and Control (CDC) 2019-11-28
2019 Cecilia Lindig-León, Sebastian Gottwald, Daniel A. Braun
Analyzing Abstraction and Hierarchical Decision-Making in Absolute Identification by Information-Theoretic Bounded Rationality
published pages: , ISSN: 1662-453X, DOI: 10.3389/fnins.2019.01230 		Frontiers in Neuroscience 13 2019-11-28
2018 Jordi Grau-Moya, Matthias Krüger, Daniel Braun
Non-Equilibrium Relations for Bounded Rational Decision-Making in Changing Environments
published pages: 1, ISSN: 1099-4300, DOI: 10.3390/e20010001 		Entropy 20/1 2019-07-08
2019 Sebastian Gottwald, Daniel A. Braun
Systems of Bounded Rational Agents with Information-Theoretic Constraints
published pages: 440-476, ISSN: 0899-7667, DOI: 10.1162/neco_a_01153 		Neural Computation 31/2 2019-06-06
2019 Sebastian Gottwald, Daniel A. Braun
Bounded Rational Decision-Making from ElementaryComputations That Reduce Uncertainty
published pages: 375, ISSN: 1099-4300, DOI: 10.3390/e21040375 		Entropy 21/4 2019-06-06
2018 Sonja Schach, Sebastian Gottwald, Daniel A. Braun
Quantifying Motor Task Performance by Bounded Rational Decision Theory
published pages: 932, ISSN: 1662-453X, DOI: 10.3389/fnins.2018.00932 		Frontiers in Neuroscience 12 2019-06-06

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