About: Fear Learning for Flexible Decision Making in RoboCup: A Discussion

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type	http://eprints.org/ontology/BookSectionEPrint http://eprints.org/ontology/EPrint Article Book Section
seeAlso	HTML Summary of #69611 Fear Learning for Flexible Decision Making in RoboCup: A Discussion
sameAs	Fear Learning for Flexible Decision Making in RoboCup: A Discussion
http://www.loc.gov...erms/relators/EDT	Flavio Tonidandel Oliver Obst Hidehisa Akiyama Claude Sammut
http://eprints.org/ontology/hasAccepted	Fear Learning for Flexible Decision Making in RoboCup: A Discussion (PDF)
http://eprints.org/ontology/hasDocument	Fear Learning for Flexible Decision Making in RoboCup: A Discussion (PDF) Fear Learning for Flexible Decision Making in RoboCup: A Discussion (Other) Fear Learning for Flexible Decision Making in RoboCup: A Discussion (Other) Fear Learning for Flexible Decision Making in RoboCup: A Discussion (Other) Fear Learning for Flexible Decision Making in RoboCup: A Discussion (Other) Fear Learning for Flexible Decision Making in RoboCup: A Discussion (Other)
dc:hasVersion	Fear Learning for Flexible Decision Making in RoboCup: A Discussion (PDF)
Title	Fear Learning for Flexible Decision Making in RoboCup: A Discussion
described by	https://demo.openlinksw.com/about/id/entity/https/raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
Date	2018-09-07
Creator	Colin G. Johnson Caroline Rizzi Patricia Vargas
status	peer reviewed published
Publisher	Springer
abstract	In this paper, we address the stagnation of RoboCup com- petitions in the fields of contextual perception, real-time adaptation and flexible decision-making, mainly in regards to the Standard Platform League (SPL). We argue that our Situation-Aware FEar Learning (SAFEL) model has the necessary tools to leverage the SPL competition in these fields of research, by allowing robot players to learn the behaviour profile of the opponent team at runtime. Later, players can use this knowledge to predict when an undesirable outcome is imminent, thus having the chance to act towards preventing it. We discuss specific scenarios where SAFEL’s associative learning could help to increase the positive outcomes of a team during a soccer match by means of contextual adaptation.
Is Part Of	Financial Cryptography and Data Security https://kar.kent.ac.uk/id/repository
Subject	QA Mathematics (inc Computing science) QA76.87 Neural computers, neural networks
list of authors	https://kar.kent.ac.uk/id/eprint/69611#authors
list of editors	https://kar.kent.ac.uk/id/eprint/69611#editors
presented at	RoboCup 2017: Robot World Cup XXI
volume	11175
is topic of	https://raw.githubusercontent.com/annajordanous/CO644Files/main/export_kar_RDFN3.n3
is primary topic of	HTML Summary of #69611 Fear Learning for Flexible Decision Making in RoboCup: A Discussion

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