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» Dynamic abstraction in reinforcement learning via clustering
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AROBOTS
2011
14 years 4 months ago
Learning GP-BayesFilters via Gaussian process latent variable models
Abstract— GP-BayesFilters are a general framework for integrating Gaussian process prediction and observation models into Bayesian filtering techniques, including particle filt...
Jonathan Ko, Dieter Fox
CDC
2009
IEEE
160views Control Systems» more  CDC 2009»
14 years 7 months ago
Exploring and exploiting routing opportunities in wireless ad-hoc networks
Abstract--In this paper, d-AdaptOR, a distributed opportunistic routing scheme for multi-hop wireless ad-hoc networks is proposed. The proposed scheme utilizes a reinforcement lear...
Abhijeet Bhorkar, Mohammad Naghshvar, Tara Javidi,...
NIPS
1993
14 years 11 months ago
Convergence of Stochastic Iterative Dynamic Programming Algorithms
Recent developments in the area of reinforcement learning have yielded a number of new algorithms for the prediction and control of Markovian environments. These algorithms,includ...
Tommi Jaakkola, Michael I. Jordan, Satinder P. Sin...
AAAI
2000
14 years 11 months ago
Unsupervised Learning and Interactive Jazz/Blues Improvisation
We present a new domain for unsupervised learning: automatically customizing the computer to a specific melodic performer by merely listening to them improvise. We also describe B...
Belinda Thom
AINTEC
2005
Springer
15 years 3 months ago
Users and Services in Intelligent Networks
— We present a vision of an Intelligent Network in which users dynamically indicate their requests for services, and formulate needs in terms of Quality of Service (QoS) and pric...
Erol Gelenbe