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Building agent teams using an explicit teamwork model and learning
1999
Artificial Intelligence
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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]
1999
Lecture Notes in Computer Science
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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]
1998
Lecture Notes in Computer Science
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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]
2000
Lecture Notes in Computer Science
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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
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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
2004
Physics of Life Reviews
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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
2007
Proceedings of the 6th international joint conference on Autonomous agents and multiagent systems - AAMAS '07
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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]
1997
arXiv
pre-print
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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
1998
The AI Magazine
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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
1999
Proceedings of the third annual conference on Autonomous Agents - AGENTS '99
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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
2020
Current Robotics Reports
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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]
2000
Lecture Notes in Computer Science
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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
2015
Social Science Research Network
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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]
2022
arXiv
pre-print
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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
2017
Artificial Intelligence
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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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