Roll Number
144190002
Category
TA
Topics for PhD Qualifiers
Compulsory Subject: (i) Optimization Techniques, (ii) Stochastic Models
Elective 1:Markov Decision Processes
Elective 2:Stochastic Optimization
Elective 1:Markov Decision Processes
Elective 2:Stochastic Optimization
Elective1
Markov Decision Processes:
Framework and some types of cost criteria: Expected total cost, Discounted cost and Average cost. Finite horizon models; Some classes of policies; Optimality of Markov policies; Dynamic programming principle and algorithm. Policy iteration, value iteration and modified policy iteration algorithms.
Framework and some types of cost criteria: Expected total cost, Discounted cost and Average cost. Finite horizon models; Some classes of policies; Optimality of Markov policies; Dynamic programming principle and algorithm. Policy iteration, value iteration and modified policy iteration algorithms.
Elective2
Stochastic Optimization:
Stochastic approximation algorithms: stability and convergence,
Markov chain Monte Carlo: variance reduction, simulated annealing,
stochastic dynamic programming, computational schemes, state and parameter estimation
Stochastic approximation algorithms: stability and convergence,
Markov chain Monte Carlo: variance reduction, simulated annealing,
stochastic dynamic programming, computational schemes, state and parameter estimation
PhD. Supervisor (if decided)
K.S. Mallikarjuna Rao