Results 1 - 10 of 562

Reinforcement Learning in the Multi-Robot Domain

by Maja J. Mataric - Autonomous Robots , 1997
"... This paper describes a formulation of reinforcement learning that enables learning in noisy, dynamic environemnts such as in the complex concurrent multi-robot learning domain. The methodology involves minimizing the learning space through the use behaviors and conditions, and dealing with the credi ..."
Abstract - Cited by 167 (20 self) - Add to MetaCart
This paper describes a formulation of reinforcement learning that enables learning in noisy, dynamic environemnts such as in the complex concurrent multi-robot learning domain. The methodology involves minimizing the learning space through the use behaviors and conditions, and dealing

Feature Selection for Activity Recognition in Multi-Robot Domains

by Douglas L. Vail, Manuela M. Veloso
"... In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that are well suited for activity recognition because they can robustly incorporate rich, non-independent features computed from ..."
Abstract - Cited by 17 (0 self) - Add to MetaCart
In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that are well suited for activity recognition because they can robustly incorporate rich, non-independent features computed

Learning in Large Cooperative Multi-Robot Domains

by F. Fernandez, L. E. Parker , 2001
"... The development of mechanisms that enable robot teams to autonomously generate cooperative behaviours is one of the most interesting issues in dis- tributed and autonomous robotic systems. In this paper, the application of reinforcement learning techniques to robot teams is studied, enabling the ..."
Abstract - Cited by 17 (2 self) - Add to MetaCart
The development of mechanisms that enable robot teams to autonomously generate cooperative behaviours is one of the most interesting issues in dis- tributed and autonomous robotic systems. In this paper, the application of reinforcement learning techniques to robot teams is studied, enabling

Action Selection via Learning Behavior Patterns in Multi-Robot Domains

by Can Erdogan, Manuela Veloso
"... The RoboCup robot soccer Small Size League has been running since 1997 with many teams successfully competing and very effectively playing the games. Teams of five robots, with a combined autonomous centralized perception and control, and distributed actuation, move at high speeds in the field space ..."
Abstract - Cited by 1 (1 self) - Add to MetaCart
as segments of interest in the logged data, and introduce a representation that captures the spatial and temporal data of the multi-robot system as instances of geometrical trajectory curves. We then learn a model of the team strategies through a variant of agglomerative hierarchical clustering. Using

c ° 1997 Kluwer Academic Publishers. Manufactured in The Netherlands. Reinforcement Learning in the Multi-Robot Domain

by P Ica, Maja J. Matari ´c , 1997
"... Abstract. This paper describes a formulation of reinforcement learning that enables learning in noisy, dynamic environments such as in the complex concurrent multi-robot learning domain. The methodology involves minimiz-ing the learning space through the use of behaviors and conditions, and dealing ..."
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Abstract. This paper describes a formulation of reinforcement learning that enables learning in noisy, dynamic environments such as in the complex concurrent multi-robot learning domain. The methodology involves minimiz-ing the learning space through the use of behaviors and conditions, and dealing

Proceedings of the Twenty-Third AAAI Conference on Artificial Intelligence (2008) Feature Selection for Activity Recognition in Multi-Robot Domains

by Douglas L. Vail, Manuela M. Veloso
"... In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that are well suited for activity recognition because they can robustly incorporate rich, non-independent features computed from ..."
Abstract - Add to MetaCart
In multi-robot settings, activity recognition allows a robot to respond intelligently to the other robots in its environment. Conditional random fields are temporal models that are well suited for activity recognition because they can robustly incorporate rich, non-independent features computed

Proceedings of the Twenty-Second International Joint Conference on Artificial Intelligence Action Selection via Learning Behavior Patterns in Multi-Robot Domains

by Can Erdogan, Manuela Veloso
"... The RoboCup robot soccer Small Size League has been running since 1997 with many teams successfully competing and very effectively playing the games. Teams of five robots, with a combined autonomous centralized perception and control, and distributed actuation, move at high speeds in the field space ..."
Abstract - Add to MetaCart
as segments of interest in the logged data, and introduce a representation that captures the spatial and temporal data of the multi-robot system as instances of geometrical trajectory curves. We then learn a model of the team strategies through a variant of agglomerative hierarchical clustering. Using

Issues in multi-robot coalition formation

by Lovekesh Vig, Julie A. Adams - IN PROC. MULTI-ROBOT SYST. FROM SWARMS TO INTELL. AUTOMATA , 2006
"... As the community strives towards autonomous multirobot systems, there is a need for these systems to autonomously form coalitions to complete assigned missions. Numerous coalition formation algorithms have been proposed in the software agent literature. Algorithms exist that form agent coalitions in ..."
Abstract - Cited by 66 (4 self) - Add to MetaCart
domain. This paper aims to bridge that discrepancy by unearthing the issues that arise while attempting to tailor these algorithms to the multi-robot domain. A well-known multi-agent coalition formation algorithm has been studied in order to identify the necessary modifications to facilitate its

A formal analysis and taxonomy of task allocation in multi-robot systems

by Brian P. Gerkey, Maja J. Matarić - INT’L. J. OF ROBOTICS RESEARCH , 2004
"... Despite more than a decade of experimental work in multi-robot systems, important theoretical aspects of multi-robot coordination mechanisms have, to date, been largely untreated. To address this issue, we focus on the problem of multi-robot task allocation (MRTA). Most work on MRTA has been ad hoc ..."
Abstract - Cited by 301 (4 self) - Add to MetaCart
Despite more than a decade of experimental work in multi-robot systems, important theoretical aspects of multi-robot coordination mechanisms have, to date, been largely untreated. To address this issue, we focus on the problem of multi-robot task allocation (MRTA). Most work on MRTA has been ad hoc

An Integrated Task Allocation Approach for Multi-Robot Navigation in Realistic Scenarios

by Antidio Viguria, Ayanna M. Howard
"... Abstract — In this paper, we discuss a distributed algorithm for task allocation that solves the Initial Formation Problem within the multi-robot domain. The algorithm has been inte-grated in a multi-robot architecture that couples the task allo-cation behavior with a path planning and navigation mo ..."
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Abstract — In this paper, we discuss a distributed algorithm for task allocation that solves the Initial Formation Problem within the multi-robot domain. The algorithm has been inte-grated in a multi-robot architecture that couples the task allo-cation behavior with a path planning and navigation
Results 1 - 10 of 562