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Building agent teams using an explicit teamwork model and learning

Milind Tambe, Jafar Adibi, Yaser Al-Onaizan, Ali Erdem, Gal A. Kaminka, Stacy C. Marsella, Ion Muslea
1999 Artificial Intelligence  
To address the challenge of teamwork, we i n vestigate a novel approach based on the reuse of a domain-independent, explicit model of teamwork, an explicitly represented hierarchy of team plans and goals  ...  Multi-agent collaboration or teamwork and learning are two critical research c hallenges in a large number of multi-agent applications.  ...  We also thank Peter Stone and Manuela Veloso for providing us player-agents of CMUnited, which provided a good opponent team to practice against in the weeks leading up to RoboCup'97.  ... 
doi:10.1016/s0004-3702(99)00022-3 fatcat:3imbg7myfnfqvdqyilrgfdsf6a

Using an Explicit Teamwork Model and Learning in RoboCup: An Extended Abstract [chapter]

Stacy Marsella, Jafar Adibi, Yaser Al-Onaizan, Ali Erdem, Randall Hill, Gal A. Kaminka, Zhun Qiu, Milind Tambe
1999 Lecture Notes in Computer Science  
We thank Bill Swartout, Paul Rosenbloom and Yigal Arens of USC ISI for their support of the RoboCup activities described in this paper.  ...  To address the challenge of teamwork, we discuss the use of a domain-independent explicit model of teamwork, and an explicit representation of team plans and goals.  ...  The key novel issues for our team in RoboCup'98 will be a further investigation of agent learning, and further analysis of teamwork related issues. 2 The ISIS Architecture An ISIS agent uses a two-tier  ... 
doi:10.1007/3-540-48422-1_19 fatcat:bxshrtmkmvdeflm7f6m46nlapu

Using an explicit model of teamwork in RoboCup [chapter]

Milind Tambe, Jafar Adibi, Yaser Al-Onaizan, All Erdem, Gal A. Kaminka, Stacy C. Marsella, Ion Muslea, Marcello Tallis
1998 Lecture Notes in Computer Science  
In terms of research accomplishments, ISIS ithstratecl the usefulness of an explicit model of teamwork both in terms of reduced development time and in,proved teamwork flexibility.  ...  ISIS also took some initial steps towards learning of individual player skills. This paper discusses the design of ISIS in detail, with particular emphasis on its novel approach to teamwork.  ...  We also thank Peter Stone and Manuela Veloso for providing us player-agents of CMUnited, which provided a good opponent team to practice against in the weeks leading up to RoboCup'97.  ... 
doi:10.1007/3-540-64473-3_54 fatcat:llr43g5jcrdi3bjisqeymaefdy

Training Teams with Collaborative Agents [chapter]

Michael S. Miller, Jianwen Yin, Richard A. Volz, Thomas R. Ioerger, John Yen
2000 Lecture Notes in Computer Science  
This paper presents an agent-based approach to designing intelligent team training systems.  ...  To carry out these functions, these agents must be equipped with an understanding of the task domain, the team structure, the selected decision-making process and their belief about other team members'  ...  Acknowledgements This research was partially supported by GANN fellowship grant P200A80305 and seed funds from the Texas Engineering Experiment Station for the Training System Sciences and Technology Initiative  ... 
doi:10.1007/3-540-45108-0_10 fatcat:ho4t2qa65rgzpnsdhfwssm2624

Index

1999 Artificial Intelligence  
Muslea Building agent teams using an explicit teamwork model and learning (2) 215-239 Uchibe, E., see Asada, M. (2) 275-292 Veloso, M., see Asada, M. (2) 193-214 Veloso, M., see Stone, P. (2) 241-273 Werger  ...  Stone, P. and M. Veloso Task decomposition, dynamic role assignment, and low-bandwidth communication for real-time strategic teamwork (2) 241-273 Tambe, M., J. Adibi, Y. Al-Onaizan, A. Erdem, G.A.  ... 
doi:10.1016/s0004-3702(99)00044-2 fatcat:al3txscacvdfbk4hsvmfvcs44y

Modeling and simulating human teamwork behaviors using intelligent agents

Xiaocong Fan, John Yen
2004 Physics of Life Reviews  
Among researchers in multi-agent systems there has been growing interest in using intelligent agents to model and simulate human teamwork behaviors.  ...  building coherent teams with both humans and agents working effectively on intelligence-intensive problems.  ...  Frank Ritter at PSU for his valuable comments and suggestions.  ... 
doi:10.1016/j.plrev.2004.10.001 fatcat:pek4lz5ubnhrnbga5jztgx4gpi

Automatic annotation of team actions in observations of embodied agents

Linus J. Luotsinen, Hans Fernlund, Ladislau Bölöni
2007 Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems - AAMAS '07  
Recognizing and annotating the occurrence of team actions in observations of embodied agents has applications in surveillance and in training of military or sport teams.  ...  The hand-crafting of these models is a difficult task of knowledge engineering, even in application domains where explicit, natural language descriptions of the team actions are available.  ...  The views and conclusions contained in this document are those of the authors and should not be interpreted as representing the official policies, either expressed or implied, of the Army Research Laboratory  ... 
doi:10.1145/1329125.1329137 dblp:conf/atal/LuotsinenFB07 fatcat:kfiblpvudvgrnhu5dk47we2k2a

Towards Flexible Teamwork [article]

M. Tambe
1997 arXiv   pre-print
Our central hypothesis is that the key to such flexibility and reusability is providing agents with general models of teamwork.  ...  The basic building block of teamwork in STEAM is joint intentions (Cohen & Levesque, 1991b); teamwork in STEAM is based on agents' building up a (partial) hierarchy of joint intentions (this hierarchy  ...  This article is an extended version of a previous conference paper (Tambe, 1997a) .  ... 
arXiv:cs/9709101v1 fatcat:mr6ukdeiencphhbmmilyjxkhou

RoboCup-97: The First Robot World Cup Soccer Games and Conferences

Itsuki Noda, Sho'ji Suzuki, Hitoshi Matsubara, Minoru Asada, Hiroaki Kitano
1998 The AI Magazine  
There were two leagues: (1) real robot and (2) simulation. Ten teams participated in the realrobot league and 29 teams in the simulation league. Over 150 researchers attended the technical workshop.  ...  The Scientific Challenge Award was given to Sean Luke (University of Maryland) for his genetic programming-based simulation team LUKE, and the Engineering Challenge Awards were given to UTTORI UNITED (  ...  Marsella, Ion Muslea, and Marcello Tallis ISIS: An Explicit Model of Teamwork at RoboCup-97 realize this behavior.  ... 
doi:10.1609/aimag.v19i3.1391 dblp:journals/aim/NodaSMAK98 fatcat:3p4grn3grnabzeuuckn4zzer6q

On being a teammate

Stacy Marsella, Jafar Adibi, Yaser Al-Onaizan, Gal A. Kaminka, Ion Muslea, Milind Tambe
1999 Proceedings of the third annual conference on Autonomous Agents - AGENTS '99  
E ective agent i n teractions in such domains raise some of most fundamental research c hallenges for agentbased systems, in teamwork, multi-agent learning and agent modeling.  ...  We compare the teams, and attempt to analyze and generalize the lessons learned. This analysis reveals several surprises, pointing out lessons for teamwork and for multi-agent learning.  ...  An agent in such domains must model other agents' behaviors, learn adapt from its interactions, form teams and act e ectively in a team, negotiate with other agents, and so on.  ... 
doi:10.1145/301136.301199 dblp:conf/agents/MarsellaAAKMT99 fatcat:sldoshu55zeihl4vpb5ba6i3fa

A Survey of Mental Modeling Techniques in Human–Robot Teaming

Aaquib Tabrez, Matthew B. Luebbers, Bradley Hayes
2020 Current Robotics Reports  
a robotic agent can act as an effective and trustworthy teammate.  ...  Summary This paper provides a structured overview of mental model theory and methodology as applied to human-robot teaming.  ...  Consider an emergency evacuation scenario, where an agent is tasked with guiding people safely out of a building.  ... 
doi:10.1007/s43154-020-00019-0 fatcat:ieaqcv5mj5fxlkq4vvbc45id6q

Toward Team-Oriented Programming [chapter]

David V. Pynadath, Milind Tambe, Nicolas Chauvat, Lawrence Cavedon
2000 Lecture Notes in Computer Science  
This paper focuses on significantly accelerating the process of building such teams using a simplified, abstract framework called team-oriented programming (TOP).  ...  In TOP, a programmer specifies an agent organization hierarchy and the team tasks for the organization to perform, abstracting away from the innumerable coordination plans potentially necessary to ensure  ...  We thank Phil Cohen, Katia Sycara and Steve Minton for collaboration on the TEAMCORE project, and for providing the Quickset, route-planner and Ariadne Web-based query agents respectively.  ... 
doi:10.1007/10719619_17 fatcat:5sj5turifzhntlc7xrea7t573y

Team Production, Endogenous Learning About Abilities and Career Concerns

Evangelia Chalioti
2015 Social Science Research Network  
This paper studies career concerns in teams where the support a worker receives depends on fellow team members'e¤ort and ability.  ...  In this setting, by exerting e¤ort and providing support, a worker can in ‡uence her own and her teammates'performances in order to bias the learning process in her favor.  ...  In team production models, the market only observes the team output and uses this (single) measure to infer the level of workers'abilities.  ... 
doi:10.2139/ssrn.2648130 fatcat:eds62yv5nvcjfnicwz7debxmbe

Semi-Supervised Imitation Learning of Team Policies from Suboptimal Demonstrations [article]

Sangwon Seo, Vaibhav V. Unhelkar
2022 arXiv   pre-print
We present Bayesian Team Imitation Learner (BTIL), an imitation learning algorithm to model the behavior of teams performing sequential tasks in Markovian domains.  ...  In contrast to existing multi-agent imitation learning techniques, BTIL explicitly models and infers the time-varying mental states of team members, thereby enabling learning of decentralized team policies  ...  Acknowledgments We thank the anonymous reviewers for their detailed and constructive feedback.  ... 
arXiv:2205.02959v5 fatcat:ep5asleudbfe3psiyjbh77a4ji

Making friends on the fly: Cooperating with new teammates

Samuel Barrett, Avi Rosenfeld, Sarit Kraus, Peter Stone
2017 Artificial Intelligence  
This algorithm is instantiated in two forms: 1) PLASTIC-Model -which builds models of previous teammates' behaviors and plans behaviors online using these models and 2) PLASTIC-Policy -which learns policies  ...  Recognizing that a key requirement of ad hoc teamwork is adaptability to previously unseen agents, the tests use more than 40 previously unknown teams on the first task and 7 previously unknown teams on  ...  Acknowledgments This work has taken place in the Learning Agents Research Group (LARG) at the Artificial Intelligence Laboratory, The University of Texas at Austin.  ... 
doi:10.1016/j.artint.2016.10.005 fatcat:ezxvbpjmszcrblqlnh6h6ye3xe
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