Search Results for author: Shyam Sudhakaran

Found 10 papers, 7 papers with code

Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs

1 code implementation17 Jul 2023 Elias Najarro, Shyam Sudhakaran, Sebastian Risi

Biological nervous systems are created in a fundamentally different way than current artificial neural networks.

Offline RL

MarioGPT: Open-Ended Text2Level Generation through Large Language Models

1 code implementation NeurIPS 2023 Shyam Sudhakaran, Miguel González-Duque, Claire Glanois, Matthias Freiberger, Elias Najarro, Sebastian Risi

MarioGPT can not only generate diverse levels, but can be text-prompted for controllable level generation, addressing one of the key challenges of current PCG techniques.

Skill Decision Transformer

no code implementations31 Jan 2023 Shyam Sudhakaran, Sebastian Risi

However many of these methods only optimize for high returns, and may not extract much information from a diverse dataset of trajectories.

D4RL Descriptive +2

Severe Damage Recovery in Evolving Soft Robots through Differentiable Programming

no code implementations14 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.

HyperNCA: Growing Developmental Networks with Neural Cellular Automata

1 code implementation25 Apr 2022 Elias Najarro, Shyam Sudhakaran, Claire Glanois, Sebastian Risi

In contrast to deep reinforcement learning agents, biological neural networks are grown through a self-organized developmental process.

reinforcement-learning Reinforcement Learning (RL)

Goal-Guided Neural Cellular Automata: Learning to Control Self-Organising Systems

1 code implementation25 Apr 2022 Shyam Sudhakaran, Elias Najarro, Sebastian Risi

Inspired by cellular growth and self-organization, Neural Cellular Automata (NCAs) have been capable of "growing" artificial cells into images, 3D structures, and even functional machines.

Variational Neural Cellular Automata

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.

Growing 3D Artefacts and Functional Machines with Neural Cellular Automata

1 code implementation15 Mar 2021 Shyam Sudhakaran, Djordje Grbic, Siyan Li, Adam Katona, Elias Najarro, Claire Glanois, Sebastian Risi

Neural Cellular Automata (NCAs) have been proven effective in simulating morphogenetic processes, the continuous construction of complex structures from very few starting cells.

Modeling natural language emergence with integral transform theory and reinforcement learning

1 code implementation30 Nov 2018 Bohdan Khomtchouk, Shyam Sudhakaran

Zipf's law predicts a power-law relationship between word rank and frequency in language communication systems and has been widely reported in a variety of natural language processing applications.

Image Classification reinforcement-learning +1

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