Reinforcement Learning in Markovian and Non-Markovian Environments

By Jürgen Schmidhuber. 1990

How researchers see this paper

The researchers whose trusted networks rank it highest, strongest advocate first. Every researcher gets a different order.

1. Liang Yu
2. Tao Jiang
3. Di Xie
4. Weiwei Xie
5. Linghua Zhang
6. Yue Zhang
7. Deng-yin Zhang
8. Zhixin Sun

Citations in the corpus

• Deep learning in neural networks: An overview (2014, neutral): “While the RNN methods above were designed for DL of temporal sequences, the Neural Heat Exchanger (Schmidhuber, 1990c) consists of two parallel deep FNNs with opposite flow directions.”
• Optimal Ordered Problem Solver (2002, neutral): “(Schmidhuber, 1991).”
• Deep Reinforcement Learning for Smart Home Energy Management (2019, background): “, approximate state [32] [33], recurrent neural networks [34], gated end-to-end memory policy networks [35], and eligibility traces [33].”