Jürgen Schmidhuber
A pioneering AI researcher and one of the inventors of LSTM. In 2018, he co-authored the paper "World Models" with David Ha.
Core Facts
The concept of world models was formally proposed by David Ha and Jürgen Schmidhuber in 2018.
The 2018 paper "World Models" by David Ha and Jürgen Schmidhuber formally introduced the concept of world models into the field of deep learning.
David Ha and Schmidhuber published the paper "World Models" in 2018, demonstrating how an agent can complete reinforcement learning training within dreams
Timeline (last 90 days)
The idea of recursive self-improvement can be traced back to the intelligence explosion hypothesis proposed by I. J. Good in 1965 and to Jürgen Schmidhuber's formalization work on self-referential improving systems.
The Gödel Machine, proposed by Jürgen Schmidhuber in 2003, is a theoretical framework for self-modifying programs that allows an agent to rewrite its own code given a formal proof that the rewrite is an improvement.
The Gödel Machine, proposed by Jürgen Schmidhuber in 2003, is a theoretical framework for a fully self-referential general problem solver.
David Ha and Jürgen Schmidhuber proposed the 'World Models' framework in 2018, using VAE and RNN to build internal representations of environments.
David Ha and Jürgen Schmidhuber proposed the 'World Models' framework in 2018, using a variational autoencoder (VAE) and a recurrent neural network (RNN) to build an internal representation of the environment.
The paper "World Models" was published by David Ha and Jürgen Schmidhuber in 2018.
World models are essentially learned dynamical equations of an environment—given the current state and action, they predict the next state.
All Facts (11)
The concept of world models was formally proposed by David Ha and Jürgen Schmidhuber in 2018.
90%VerifiedThe 2018 paper "World Models" by David Ha and Jürgen Schmidhuber formally introduced the concept of world models into the field of deep learning.
75%VerifiedDavid Ha and Schmidhuber published the paper "World Models" in 2018, demonstrating how an agent can complete reinforcement learning training within dreams
75%VerifiedDavid Ha and Jürgen Schmidhuber proposed the 'World Models' framework in 2018, using VAE and RNN to build internal representations of environments.
65%VerifiedWorld models are essentially learned dynamical equations of an environment—given the current state and action, they predict the next state.
65%UnverifiedLSTM was proposed by Hochreiter and Schmidhuber in 1997, and its gating mechanism solved the vanishing gradient problem of standard RNNs.
60%UnverifiedThe idea of recursive self-improvement can be traced back to the intelligence explosion hypothesis proposed by I. J. Good in 1965 and to Jürgen Schmidhuber's formalization work on self-referential improving systems.
50%UnverifiedThe Gödel Machine, proposed by Jürgen Schmidhuber in 2003, is a theoretical framework for self-modifying programs that allows an agent to rewrite its own code given a formal proof that the rewrite is an improvement.
50%UnverifiedThe Gödel Machine, proposed by Jürgen Schmidhuber in 2003, is a theoretical framework for a fully self-referential general problem solver.
50%UnverifiedDavid Ha and Jürgen Schmidhuber proposed the 'World Models' framework in 2018, using a variational autoencoder (VAE) and a recurrent neural network (RNN) to build an internal representation of the environment.
50%UnverifiedThe paper "World Models" was published by David Ha and Jürgen Schmidhuber in 2018.
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