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    NIPS
    1998
    88views Information Technology» more  NIPS 1998»
    Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts
    14 years 1 months ago
    Scheduling Straight-Line Code Using Reinforcement Learning and Rollouts
    Download  www.cs.ou.edu
    The execution order of a block of computer instructions can make a difference in its running time by a factor of two or more. In order to achieve the best possible speed, compiler...
    Amy McGovern, J. Eliot B. Moss
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    NIPS
    1998
    140views Information Technology» more  NIPS 1998»
    Gradient Descent for General Reinforcement Learning
    14 years 1 months ago
    Gradient Descent for General Reinforcement Learning
    Download  www.ri.cmu.edu
    A simple learning rule is derived, the VAPS algorithm, which can be instantiated to generate a wide range of new reinforcementlearning algorithms. These algorithms solve a number ...
    Leemon C. Baird III, Andrew W. Moore
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    FLAIRS
    1998
    130views Artificial Intelligence» more  FLAIRS 1998»
    Learning to Race: Experiments with a Simulated Race Car
    14 years 1 months ago
    Learning to Race: Experiments with a Simulated Race Car
    Download  www.aaai.org
    Our focus is on designing adaptable agents for highly dynamic environments. Wehave implementeda reinforcement learning architecture as the reactive componentof a twolayer control ...
    Larry D. Pyeatt, Adele E. Howe
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    FLAIRS
    1998
    90views Artificial Intelligence» more  FLAIRS 1998»
    Optimizing Production Manufacturing Using Reinforcement Learning
    14 years 1 months ago
    Optimizing Production Manufacturing Using Reinforcement Learning
    Download  www.aaai.org
    Manyindustrial processes involve makingparts with an assemblyof machines, where each machinecarries out an operation on a part, and the finished product requires a wholeseries of ...
    Sridhar Mahadevan, Georgios Theocharous
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    NIPS
    2003
    105views Information Technology» more  NIPS 2003»
    Gaussian Processes in Reinforcement Learning
    14 years 1 months ago
    Gaussian Processes in Reinforcement Learning
    Download  books.nips.cc
    We exploit some useful properties of Gaussian process (GP) regression models for reinforcement learning in continuous state spaces and discrete time. We demonstrate how the GP mod...
    Carl Edward Rasmussen, Malte Kuss
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    IJCAI
    2003
    130views Artificial Intelligence» more  IJCAI 2003»
    Multiple-Goal Reinforcement Learning with Modular Sarsa(0)
    14 years 1 months ago
    Multiple-Goal Reinforcement Learning with Modular Sarsa(0)
    Download  www.cc.gatech.edu
    We present a new algorithm, GM-Sarsa(0), for finding approximate solutions to multiple-goal reinforcement learning problems that are modeled as composite Markov decision processe...
    Nathan Sprague, Dana H. Ballard
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    ICMLA
    2003
    169views Machine Learning» more  ICMLA 2003»
    Reinforcement Learning Task Clustering
    14 years 1 months ago
    Reinforcement Learning Task Clustering
    Download  james.jlcarroll.net
    This work represents the first step towards a task library system in the reinforcement learning domain. Task libraries could be useful in speeding up the learning of new tasks th...
    James L. Carroll, Todd S. Peterson, Kevin D. Seppi
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    ICMLA
    2003
    159views Machine Learning» more  ICMLA 2003»
    A Distributed Reinforcement Learning Approach to Pattern Inference in Go
    14 years 1 months ago
    A Distributed Reinforcement Learning Approach to Pattern Inference in Go
    Download  mysite.verizon.net
    — This paper shows that the distributed representation found in Learning Vector Quantization (LVQ) enables reinforcement learning methods to cope with a large decision search spa...
    Myriam Abramson, Harry Wechsler
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    NCI
    2004
    185views Neural Networks» more  NCI 2004»
    Hierarchical reinforcement learning with subpolicies specializing for learned subgoals
    14 years 1 months ago
    Hierarchical reinforcement learning with subpolicies specializing for learned subgoals
    Download  staff.science.uva.nl
    This paper describes a method for hierarchical reinforcement learning in which high-level policies automatically discover subgoals, and low-level policies learn to specialize for ...
    Bram Bakker, Jürgen Schmidhuber
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    ESANN
    2003
    152views Neural Networks» more  ESANN 2003»
    Improving iterative repair strategies for scheduling with the SVM
    14 years 1 months ago
    Improving iterative repair strategies for scheduling with the SVM
    Download  www2.in.tu-clausthal.de
    The resource constraint project scheduling problem (RCPSP) is an NP-hard benchmark problem in scheduling which takes into account the limitation of resources’ availabilities in ...
    Kai Gersmann, Barbara Hammer
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