DRL-STAF uses deep RL to predict observations and estimate discrete hidden states for multivariate hidden Markov processes, outperforming HMMs, deep learning models, and hybrids in experiments.
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DRL-STAF: A Deep Reinforcement Learning Framework for State-Aware Forecasting of Complex Multivariate Hidden Markov Processes
DRL-STAF uses deep RL to predict observations and estimate discrete hidden states for multivariate hidden Markov processes, outperforming HMMs, deep learning models, and hybrids in experiments.