[Lisa_seminaires] NEW LOCATION: UdeM-McGill-MITACS machine learning seminar Tues April 8th, 10am, MC103

Hugo Larochelle larocheh at iro.umontreal.ca
Jeu 3 Avr 11:15:36 EDT 2008


Next week's seminar (see http://www.iro.umontreal.ca/article.php3? 
id_article=107&lang=en):


Aggregate Markov Decision Processes


by Hasan Mirza,
McGill University

Location: McConnell Engineering (McGill), room 103
Time: April 8th 2008, 10am

We consider a special type of Markov decision problem in which an  
agent maintains an infiitely divisible collection of identical  
"machines," each described by a standard finite-state MDP. The agent  
is subject to constraints on fraction of the machines receiving each  
available action. We model the collection of MDPs as a single MDP by  
looking at the frequency at which each state is observed in each  
underlying MDP. Although this MDP has continuous state and action  
spaces, its transitions are deterministic, and its structure leads to  
interesting properties such as a convex value function. We present a  
linear-programming receding-horizon control technique for use under  
the discountedcost performance criterion, and investigate its  
behaviour through experiments on example problems. The experimental  
results show that the technique is viable on practically-sized  
problems. Finally, we present a probabilistic result that relates the  
frequency MDP to the model where each machine is treated separately  
and the collection is not infinitely divisible.


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