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BRISC SIGNED

Bounded Rationality in Sensorimotor Coordination

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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.

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

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

 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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