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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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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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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GoodAI presents a new paper to trace memetic evolution and investigate whether open-ended learning algorithms can be discovered through the lens of socio-cultural learning models.
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We recently held the Badger Seminar titled: Beyond Life-long Learning via Modular Meta-Learning, with participants joining online and at our headquarters in Prague.
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We are very proud that Nicholas Guttenberg, Senior Research Scientist at GoodAI, recently won the Evocraft 2021 competition - the Minecraft Open-Endedness Challenge!
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Progress from recent experiments.
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In 2021/22 GoodAI will focus on four core research areas: learning to learn, lifelong (gradual) learning, open-endedness, and generalization / extrapolation of meta-learned algorithms.
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Game developers at Keen Software House (sister company of GoodAI) have used Manual Badger architecture to evaluate parallelization techniques that would benefit the future development of Space Engineers.
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Dr. Kai Arulkumaran of Araya has received a grant from GoodAI in order to apply open-ended algorithms to generating video game content (such as spaceships and space stations) in the sandbox game Space Engineers.
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