Adaptive Learning needs Attention, Meta-learning and Working Memory

We tested which model mechanisms best explain how six animals learn attention sets and found a common set of most-important behavioral mechanisms that account for learning success.
When learning attention sets is easy value based reinforcement learning and working memory are powerful, but when learning problems are more complex learning is more efficient with attention and a meta-learning process that help speeding up learning when errors accumulate. (See our paper Womelsdorf at al. (2022) Learning at variable attentional load requires cooperation between working memory, meta-learning and attention-augmented reinforcement learning. Journal of Cognitive Neuroscience 34(1) 79-107.)

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3 minute Thesis Competition

Congratulations to Ben to win the York University 3 minute thesis competition in presenting his MSc graduation work ! Here is the University’s press release about the 2016 YorkU 3MT Winner ! Good luck from the laboratory when moving to the provincial level competition (still with only 3 minutes…for the whole thesis).

New Open-Source Experimental Suite for 3D experiments in monkeys, humans, and artificially intelligent agents

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