Tag: Research

Building for Intelligence: Cells to Societies Workshop Notes

June 22, 2022 ResearchTechnical blogs

An overview of research findings from the 2022 ICLR workshop exploring the cumulative nature of culture across disciplines.

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Policy Learning with Neural Cellular Automata

April 19, 2022 ResearchTechnical blogs

GoodAI grantee Sebastian Risi will conduct research to optimize neural cellular automata (NCA) to grow neural networks.

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A Conversation with Ted Chiang

April 11, 2022 InterviewResearch

Rethinking the learning framework. What would that look like in AI?

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A Conversation with Mayalen Etcheverry

Developing "curious" AI agents to autonomously discover and learn a diversity of structures and skills in their environments.

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A Conversation with Michael Levin

Evolution doesn't produce specific solutions to specific environmental problems. It produces problem solving machines. Machines that can solve problems in other spaces.

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What are the differences between centralized learning (in monolithic systems) and decentralized learning (in multi-agent systems)?

January 18, 2022 ResearchTechnical blogs

Why are we studying social learning in multi-agent systems?

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Open Call for Papers for 2022 ICLR Workshop on Collective Learning

December 23, 2021 ResearchTechnical blogs

The 2022 workshop, “From Cells to Societies: Collective Learning Across Scales,” will examine natural systems to understand how collective interactions can contribute to new learning approaches in artificial learning systems.

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GPU Grant to Support TU Delft’s AI Research

November 30, 2021 ResearchTechnical blogs

Wendelin Böhmer investigates how restricted neural modules, similar to Badger agents, can learn generalizing sub-tasks and how a message passing architecture can reliably compose their output for out-of-distribution generalization.

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Bridging the Continual Learning Gap with Deep Artificial Neurons

October 26, 2021 ResearchTechnical blogs

Integrating GoodAI’s Badger architecture and principles, new grant recipients Rolando Estrada and Blake Camp aim to develop a continual semi-supervised learning system capable of joint supervised and unsupervised learning.

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