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eess.SY2020
On Determining and Qualifying the Number of Superstates in Aggregation of Markov Chains
Amber Srivastava, Raj K. Velicheti, Srinivasa M. Salapaka
Many studies involving large Markov chains require determining a smaller representative (aggregated) chains. Each {\em superstate} in the representative chain represents a {\em gro…
cs.LG2020
Parameterized MDPs and Reinforcement Learning Problems -- A Maximum Entropy Principle Based Framework
Amber Srivastava, Srinivasa M Salapaka
We present a framework to address a class of sequential decision making problems. Our framework features learning the optimal control policy with robustness to noisy data, determin…
math.OC2020
Inequality Constraints in Facility Location and Other Similar Optimization Problems: An Entropy Based Approach
Amber Srivastava, Gabriel Barsi Haberfeld, Naira Hovakimyan +1
In this paper we propose an annealing based framework to incorporate inequality constraints in optimization problems such as facility location, simultaneous facility location with…