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PILOT: An Actor-oriented Learning and Optimization Toolkit for Robotic Swarm Applications
Ilge Akkaya, Shuhei Emoto, Edward A. Lee

Citation
Ilge Akkaya, Shuhei Emoto, Edward A. Lee. "PILOT: An Actor-oriented Learning and Optimization Toolkit for Robotic Swarm Applications". Second International Workshop on Robotic Sensor Networks (RSN'15), Cyber-Physical Systems Week 2015, 13, April, 2015.

Abstract
We present PILOT (Ptolemy Inference, Learning, and Optimization Toolkit), an actor-oriented machine learning and optimization toolkit that is designed for developing data intensive distributed applications for sensor networks. We de- fine an actor interface that bridges state-space models for robotic control problems and a collection of machine learning and optimization algorithms, then demonstrate how the framework leverages programmability of sophisticated distributed robotic applications on streaming data. As a case study, we consider a cooperative target tracking scenario and study how the framework enables adaptation and implementation of control policies and simulation within environmental constraints by presenting actor-oriented abstractions that enable application developers to build state-space aware machine learning and optimization actors.

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Citation formats  
  • HTML
    Ilge Akkaya, Shuhei Emoto, Edward A. Lee. <a
    href="http://chess.eecs.berkeley.edu/pubs/1078.html"
    >PILOT: An Actor-oriented Learning and Optimization
    Toolkit for Robotic Swarm Applications</a>, Second
    International Workshop on Robotic Sensor Networks (RSN'15),
    Cyber-Physical Systems Week 2015, 13, April, 2015.
  • Plain text
    Ilge Akkaya, Shuhei Emoto, Edward A. Lee. "PILOT: An
    Actor-oriented Learning and Optimization Toolkit for Robotic
    Swarm Applications". Second International Workshop on
    Robotic Sensor Networks (RSN'15), Cyber-Physical Systems
    Week 2015, 13, April, 2015.
  • BibTeX
    @inproceedings{AkkayaEmotoLee15_PILOTActororientedLearningOptimizationToolkitForRobotic,
        author = {Ilge Akkaya and Shuhei Emoto and Edward A. Lee},
        title = {PILOT: An Actor-oriented Learning and Optimization
                  Toolkit for Robotic Swarm Applications},
        booktitle = {Second International Workshop on Robotic Sensor
                  Networks (RSN'15)},
        organization = {Cyber-Physical Systems Week 2015},
        day = {13},
        month = {April},
        year = {2015},
        abstract = {We present PILOT (Ptolemy Inference, Learning, and
                  Optimization Toolkit), an actor-oriented machine
                  learning and optimization toolkit that is designed
                  for developing data intensive distributed
                  applications for sensor networks. We de- fine an
                  actor interface that bridges state-space models
                  for robotic control problems and a collection of
                  machine learning and optimization algorithms, then
                  demonstrate how the framework leverages
                  programmability of sophisticated distributed
                  robotic applications on streaming data. As a case
                  study, we consider a cooperative target tracking
                  scenario and study how the framework enables
                  adaptation and implementation of control policies
                  and simulation within environmental constraints by
                  presenting actor-oriented abstractions that enable
                  application developers to build state-space aware
                  machine learning and optimization actors.},
        URL = {http://chess.eecs.berkeley.edu/pubs/1078.html}
    }
    

Posted by Ilge Akkaya on 27 Oct 2014.
Groups: ptolemy
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