The two-dimensional organization of behavior

By Mark B. Ring, Tom Schaul, J. Urgen Schmidhuber. 2011

20 citations recorded by the source corpus.

Subfields: Artificial Intelligence, Cognitive Neuroscience

How researchers see this paper

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

In Artificial Intelligence

1. Filipe Wall Mutz
2. J. Urgen Schmidhuber
3. Paulo E. Rauber
4. Sergey Levine
5. David R Ha
6. Alex Graves
7. Yoshua Bengio
8. Pieter Abbeel

In Cognitive Neuroscience

1. J. Urgen Schmidhuber
2. Faustino J. Gomez
3. Jan Koutník
4. Olof Mogren

Citations in the corpus

• Deep learning in neural networks: An overview (2014, background): “Recent HRL organizes potentially deep NN-based RL sub-modules into self-organizing, 2-dimensional motor control maps (Ring et al., 2011) inspired by neurophysiological findings (Graziano, 2009).”
• On Learning to Think: Algorithmic Information Theory for Novel Combinations of Reinforcement Learning Controllers and Recurrent Neural World Models (2015, background): “Recent HRL organizes potentially deep NNbased RL sub-modules into self-organizing, 2-dimensional motor control maps [203] inspired by neurophysiological findings [81].”
• Self-Delimiting Neural Networks (2012, background): “The underlying cause of such neighborhood-preserving weight matrices, however, will not be a traditional pre-wired neighborhood-enforcing learning rule [33, 46], but sheer efficiency per se .”
• Hindsight policy gradients (2017, background): “An interesting application for goal-conditional policies is hierarchical reinforcement learning [12–30], where they may help in defining options for arbitrary subgoals [22].”