no code implementations • 21 Jul 2022 • Md Umar Hashmi, Deepjyoti Deka, Ana Bušić, Dirk Van Hertem
To mitigate issues related to the growth of variable smart loads and distributed generation, distribution system operators (DSO) now make it binding for prosumers with inverters to operate under pre-set rules.
no code implementations • 12 Aug 2021 • Austin Coffman, Ana Bušić, Prabir Barooah
The framework enables coordination of an arbitrary number of TCLs that: (i) is computationally efficient, (ii) is implementable at the TCLs with local feedback and low communication, and (iii) enables reference tracking by the collection while ensuring that temperature and cycling constraints are satisfied at every TCL at all times.
no code implementations • 7 Feb 2020 • Shuhang Chen, Adithya M. Devraj, Ana Bušić, Sean Meyn
This is motivation for the focus on mean square error bounds for parameter estimates.
no code implementations • NeurIPS 2020 • Shuhang Chen, Adithya M. Devraj, Fan Lu, Ana Bušić, Sean P. Meyn
Based on multiple experiments with a range of neural network sizes, it is found that the new algorithms converge quickly and are robust to choice of function approximation architecture.
no code implementations • 25 Apr 2019 • Shuhang Chen, Adithya M. Devraj, Ana Bušić, Sean P. Meyn
The objective in this paper is to obtain fast converging reinforcement learning algorithms to approximate solutions to the problem of discounted cost optimal stopping in an irreducible, uniformly ergodic Markov chain, evolving on a compact subset of $\mathbb{R}^n$.
no code implementations • 17 Sep 2018 • Adithya M. Devraj, Ana Bušić, Sean Meyn
There are two well known SA techniques that are known to have optimal asymptotic variance: the Ruppert-Polyak averaging technique, and stochastic Newton-Raphson (SNR).