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  1. IEEE Workshop on Robotic Intelligence in Informationally Structured Space, RIISS.
  2. 2013 IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS)
  3. A concurrent approach to robot team learning
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2014 IEEE Symposium on Robotic Intelligence in Informationally Structured Space (RiiSS)
2013 IEEE Workshop on Robotic Intelligence in Informationally Structured Space (RiiSS)
Slip detection using robot fingertip with 6-axis force/torque sensor
Application of magnetic type tactile sensor to gripper
Cyclic motion generation for intelligent robot by evolutionary computation
Estimation of joint force/torque based on EMG signals
Fuzzy logic temperature controller for small robots
Adaptive and safe mobile manipulator for human robot interaction
EMG-EMG correlation analysis for human hand movements
Evolutionary conditions for the emergence of robotic theory of mind with multiple goals
A concurrent approach to robot team learning
Biological inspired human action recognition
Approaches to dynamic team sizes
Reinforcement learning-based robust adaptive tracking control for multi-wheeled mobile robots synchronization with optimality
A distributed multi robot SLAM system for environment learning
Integration of behaviors and languages with a hierarchal structure self-organized in a neuro-dynamical model
Developing an information giving system for supporting community society
Maritime space understanding using multiple radar systems by iterative image reconstuction algorithm
A path planning behavior learning of six legged robot based on human teaching model
Proposal of learning method which selects objectives based on the state
Learning based robot control with sequential Gaussian process
2011 IEEE Workshop on Robotic Intelligence In Informationally Structured Space
2009 IEEE Workshop on Robotic Intelligence in Informationally Structured Space

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A concurrent approach to robot team learning

Content Provider IEEE Xplore Digital Library
Author Ng, L. Reza Emami, M.
Copyright Year 2013
Description Author affiliation: Inst. for Aerosp. Studies, Univ. of Toronto, Toronto, ON, Canada (Ng, L.; Reza Emami, M.)
Abstract Despite the advancement of research and development on multi-robot teams, a key challenge still remains as to how to develop effective mechanisms that enable the robots to autonomously generate, adapt, and enhance team behaviours while improving their individual performance simultaneously. To address this issue, a cooperative learning algorithm is modified in this paper to accommodate for the individualistic Q-Learning as well as the collaborative advice sharing. The developed methods are examined in relation to the performance characteristics of single-robot learning to ascertain if they retain viable learning characteristics despite the integration of individual learning into team behaviour. Further, a modification to the individual learning method was implemented into the proposed multi-robot learning approach to examine the performance improvements gained by the multi-robot learning algorithms.
Starting Page 50
Ending Page 57
File Size 1293321
Page Count 8
File Format PDF
ISBN 9781467358774
DOI 10.1109/RiiSS.2013.6607929
Language English
Publisher Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Publisher Date 2013-04-16
Publisher Place Singapore
Access Restriction Subscribed
Rights Holder Institute of Electrical and Electronics Engineers, Inc. (IEEE)
Subject Keyword Learning systems robot team Conferences Collaboration cooperative learning Learning (artificial intelligence) collaborative learning multi-agent algorithm Robots Standards Equations reinforcement learning
Content Type Text
Resource Type Article
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