MuZero matches or exceeds AlphaZero-level performance in Go, Chess, Shogi and sets a new state of the art on 57 Atari games by learning a model that directly supports planning rather than reconstructing full environment dynamics.
Imagenet classification with deep convolutional neural networks
2 Pith papers cite this work. Polarity classification is still indexing.
2
Pith papers citing it
years
2019 2representative citing papers
RNN and LSTM models outperform other algorithms in predicting stream flow from precipitation, land use, and temperature, with a public dataset released.
citing papers explorer
-
Mastering Atari, Go, Chess and Shogi by Planning with a Learned Model
MuZero matches or exceeds AlphaZero-level performance in Go, Chess, Shogi and sets a new state of the art on 57 Atari games by learning a model that directly supports planning rather than reconstructing full environment dynamics.
-
Water Preservation in Soan River Basin using Deep Learning Techniques
RNN and LSTM models outperform other algorithms in predicting stream flow from precipitation, land use, and temperature, with a public dataset released.