no code implementations • 14 Jun 2022 • Kazuya Horibe, Kathryn Walker, Rasmus Berg Palm, Shyam Sudhakaran, Sebastian Risi
Biological systems are very robust to morphological damage, but artificial systems (robots) are currently not.
no code implementations • 31 May 2022 • Miguel González-Duque, Rasmus Berg Palm, Søren Hauberg, Sebastian Risi
Deep generative models can automatically create content of diverse types.
1 code implementation • 14 Mar 2022 • Kathryn Walker, Rasmus Berg Palm, Rodrigo Moreno Garcia, Andres Faina, Kasper Stoy, Sebastian Risi
Materials with the ability to self-classify their own shape have the potential to advance a wide range of engineering applications and industries.
1 code implementation • ICLR 2022 • Rasmus Berg Palm, Miguel González-Duque, Shyam Sudhakaran, Sebastian Risi
Additionally, we show that the VNCA can learn a distribution of stable attractors that can recover from significant damage.
no code implementations • 18 May 2021 • Miguel González-Duque, Rasmus Berg Palm, Sebastian Risi
Current systems for DDA rely on expensive data mining, or on hand-crafted rules designed for particular domains, and usually adapts to keep players in the flow, leaving no room for the designer to present content that is purposefully easy or difficult.
1 code implementation • 8 Dec 2020 • Djordje Grbic, Rasmus Berg Palm, Elias Najarro, Claire Glanois, Sebastian Risi
In contrast to previous work in Minecraft that focused on learning to play the game, the grand challenge we pose here is to automatically search for increasingly complex artifacts in an open-ended fashion.
1 code implementation • 23 Nov 2020 • Thor V. A. N. Olesen, Dennis T. T. Nguyen, Rasmus Berg Palm, Sebastian Risi
Planning is a powerful approach to reinforcement learning with several desirable properties.
1 code implementation • 13 Nov 2020 • Rasmus Berg Palm, Elias Najarro, Sebastian Risi
We test this hypothesis by decoupling the number of Hebbian learning rules from the number of synapses and systematically varying the number of Hebbian learning rules.
1 code implementation • 15 May 2020 • Miguel González-Duque, Rasmus Berg Palm, David Ha, Sebastian Risi
The approach can reliably find levels with a specific target difficulty for a variety of planning agents in only a few trials, while maintaining an understanding of their skill landscape.
2 code implementations • 18 Dec 2018 • Rasmus Berg Palm, Florian Laws, Ole Winther
We believe our proposed architecture can be used on many real life information extraction tasks where word classification cannot be used due to a lack of the required word-level labels.
1 code implementation • ICLR 2018 • Rasmus Berg Palm, Ulrich Paquet, Ole Winther
Humans possess an ability to abstractly reason about objects and their interactions, an ability not shared with state-of-the-art deep learning models.
6 code implementations • NeurIPS 2018 • Rasmus Berg Palm, Ulrich Paquet, Ole Winther
We achieve state of the art results on the bAbI textual question-answering dataset with the recurrent relational network, consistently solving 20/20 tasks.
Ranked #3 on Question Answering on bAbi (Mean Error Rate metric)
1 code implementation • 24 Aug 2017 • Rasmus Berg Palm, Ole Winther, Florian Laws
We describe a recurrent neural network model that can capture long range context and compare it to a baseline logistic regression model corresponding to the current CloudScan production system.
1 code implementation • WS 2017 • Rasmus Berg Palm, Dirk Hovy, Florian Laws, Ole Winther
End-to-end (E2E) models, which take raw text as input and produce the desired output directly, need not depend on token-level labels.