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From ‘CyberSlug’ to ‘CyberOctopus’: New AI explores, remembers, seeks novelty, overcomes obstacles

by Diana Yates  | Life Sciences Editor, U. of I. News Bureau

By giving artificial intelligence simple associative learning rules based on the brain circuits that allow a sea slug to forage — and augmenting it with better episodic memory, like that of an octopus — scientists have built an AI that can navigate new environments, seek rewards, map landmarks and overcome obstacles.

Professor Rhanor Gillette and Ekaterina Gribkova
Researchers use lessons learned from the foraging behaviors of octopus and other invertebrate creatures to create new approaches for AI programming using the biologically inspired, bottom-up enhancement of AI for higher-order cognition.
Photo taken at the University of Illinois Urbana-Champaign on Tuesday, June 18, 2024.
(Photo by Fred Zwicky / University of Illinois Urbana-Champaign)

Reported in the journal Neurocomputing, the new approach gives AI the ability to explore and gather the information it needs to expand its spatial and temporal awareness, growing its knowledge base while learning on the job, said Ekaterina Gribkova, a postdoctoral researcher at the University of Illinois Urbana-Champaign who led the study with U. of I. molecular and integrative physiology professor emeritus Rhanor Gillette, with support from agricultural and biological engineering professor Girish Chowdhary

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The paper “Cognitive mapping and episodic memory emerge from simple associative learning rules” is available online
DOI: 10.1016/j.neucom.2024.127812

Gillette and Gribkova are affiliates of the Center for Artificial Intelligence Innovation at the National Center for Supercomputing Applications and in the Neuroscience Program at the U. of I. Gillette also is a professor in the Beckman Institute for Advanced Science and Technology and in the Carl R. Woese Institute for Genomic Biology at Illinois.