Parameter learning of stochastic Boolean networks
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DOI: 10.1002/rnc.5755
Abstract: In this article, the parameter learning problem is studied for stochastic Boolean networks (SBNs). Both the measure noise and the system noise are assumed to be white and modeled by sequences of Bernoulli distributed stochastic… read more here.
Keywords: boolean networks; parameter learning; stochastic boolean; learning stochastic ... See more keywords
Iterative Learning Stochastic MPC with Adaptive Constraint Tightening for Building HVAC Systems
Sign Up to like & getrecommendations! Published in 2020 at "IFAC-PapersOnLine"
DOI: 10.1016/j.ifacol.2020.12.636
Abstract: Abstract Most of the existing stochastic model predictive control (SMPC) algorithms for systems subject to random disturbance are designed offline using the distribution information of the uncertainties. In this paper, we propose an iterative learning… read more here.
Keywords: iterative learning; adaptive constraint; learning stochastic; constraint tightening ... See more keywords
Decentralized Q-Learning for Stochastic Teams and Games
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DOI: 10.1109/tac.2016.2598476
Abstract: There are only a few learning algorithms applicable to stochastic dynamic teams and games which generalize Markov decision processes to decentralized stochastic control problems involving possibly self-interested decision makers. Learning in games is generally difficult… read more here.
Keywords: decision; teams games; decision makers; learning stochastic ... See more keywords