Using an explicit teamwork model and learning in robocup

Stacy Marsella, Jafar Adibi, Yaser Al-Onaizan, Ali Erdem, Randall Hill, Gal A. Kaminka, Zhun Qiu, Milind Tambe

Research output: Chapter in Book/Report/Conference proceedingChapterpeer-review

Abstract

The RoboCup research initiative has established synthetic and robotic soccer as testbeds for pursuing research challenges in Articial Intelligence and robotics. This extended abstract focuses on teamwork and learning, two of the multi- agent research challenges highlighted in RoboCup. To address the challenge of teamwork, we discuss the use of a domain-independent explicit model of team- work, and an explicit representation of team plans and goals. We also discuss the application of agent learning in RoboCup.
Original languageAmerican English
Title of host publicationRobot Soccer World Cup
EditorsMinoru Asada, Hiroaki Kitano
PublisherSpringer Berlin Heidelberg
Pages237-245
ISBN (Print)978-3-540-48422-6
StatePublished - 1998

Publication series

NameLecture Notes in Computer Science
Volume1604

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