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» Coarticulation in Markov Decision Processes
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AIPS
2007
13 years 11 months ago
Learning to Plan Using Harmonic Analysis of Diffusion Models
This paper summarizes research on a new emerging framework for learning to plan using the Markov decision process model (MDP). In this paradigm, two approaches to learning to plan...
Sridhar Mahadevan, Sarah Osentoski, Jeffrey Johns,...
AAAI
2010
13 years 10 months ago
PUMA: Planning Under Uncertainty with Macro-Actions
Planning in large, partially observable domains is challenging, especially when a long-horizon lookahead is necessary to obtain a good policy. Traditional POMDP planners that plan...
Ruijie He, Emma Brunskill, Nicholas Roy
IJCAI
2003
13 years 10 months ago
A Planning Algorithm for Predictive State Representations
We address the problem of optimally controlling stochastic environments that are partially observable. The standard method for tackling such problems is to define and solve a Part...
Masoumeh T. Izadi, Doina Precup
CORR
2010
Springer
88views Education» more  CORR 2010»
13 years 9 months ago
Multiple Timescale Dispatch and Scheduling for Stochastic Reliability in Smart Grids with Wind Generation Integration
Integrating volatile renewable energy resources into the bulk power grid is challenging, due to the reliability requirement that at each instant the load and generation in the syst...
Miao He, Sugumar Murugesan, Junshan Zhang
TMC
2011
219views more  TMC 2011»
13 years 3 months ago
Optimal Channel Access Management with QoS Support for Cognitive Vehicular Networks
We consider the problem of optimal channel access to provide quality of service (QoS) for data transmission in cognitive vehicular networks. In such a network the vehicular nodes ...
Dusit Niyato, Ekram Hossain, Ping Wang