On Learning to Think: Algorithmic Information Theory for Novel - - PowerPoint PPT Presentation

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On Learning to Think: Algorithmic Information Theory for Novel - - PowerPoint PPT Presentation

Oct 13, 2023 361 likes •541 views

On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models Jrgen Schmidhuber The Swiss AI Lab IDSIA Univ. Lugano & SUPSI

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Jürgen Schmidhuber The Swiss AI Lab IDSIA

  • Univ. Lugano & SUPSI

http://www.idsia.ch/~juergen On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models NNAISENSE

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Jürgen Schmidhuber You_again Shmidhoobuh

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With Hochreiter (1997), Gers (2000), Graves, Fernandez, Gomez, Bayer…

1997-2009. Since 2015 on your phone! Google, Microsoft, IBM, Apple, all use LSTM now

http://www.idsia.ch/~juergen/rnn.html

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LSTM learns knot-tying tasklets: Mayr Gomez Wierstra Nagy Knoll Schmidhuber, IROS’06

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2005: Reinforcement- Learning or Evolving RNNs with Fast Weights

Robot learns to balance 1 or 2 poles through 3D joint

http://www.idsia.ch/~juergen/evolution.html

Gomez & Schmidhuber: Co-evolving recurrent neurons learn deep memory POMDPs. GECCO 2005

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Finds Complex Neural Controllers with a Million Weights – RAW VIDEO INPUT! Faustino Gomez, Jan Koutnik, Giuseppe Cuccu, J. Schmidhuber, GECCO, July 2013 Reinforcement Learning in Partially Observable Worlds

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J.S.: IJCNN 1990, NIPS 1991: Reinforcement Learning with Recurrent Controller & Recurrent World Model

Learning and planning with recurrent networks

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IJNS 1991: R-Learning of Visual Attention

  • n 100,000 times slower computers

http://people.idsia.ch/~juergen/attentive.html

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1991: current goal=extra fixed input 2015: all of this is coming back!

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RoboCup World Champion 2004, Fastest League, 5m/s Alex @ IDSIA, led FU Berlin’s RoboCup World Champion Team 2004 Lookahead expectation & planning with neural networks (Schmidhuber, IEEE INNS 1990): successfully used for RoboCup by Alexander Gloye-Förster (went to IDSIA) http://www.idsia.ch/~juergen/learningrobots.html

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RNNAIssance 2014-2015 On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning RNN- based Controllers (RNNAIs) and Recurrent Neural World Models

http://arxiv.org/abs/1511.09249

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Formal theory of fun & novelty & surprise & attention & creativity & curiosity & art & science & humor Maximize Future Fun(Data X,O(t))~ ∂CompResources(X,O(t))/∂t

E.g., Connection Science 18(2):173-187, 2006 IEEE Transactions AMD 2(3):230-247, 2010 http://www.idsia.ch/~juergen/creativity.html

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https://www.youtube.com/watch?v=OTqdXbTEZpE Continual curiosity-driven skill acquisition from high-dimensional video inputs for humanoid robots. Kompella, Stollenga, Luciw,

  • Schmidhuber. Artificial Intelligence,

2015

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now talking to investors

neural networks-based artificial intelligence

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NIPS 2016 demo: Reinforcement learning to park Cooperation NNAISENSE - AUDI

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