Ari Weinstein
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View article: Intuitive physics learning in a deep-learning model inspired by developmental psychology
Intuitive physics learning in a deep-learning model inspired by developmental psychology Open
‘Intuitive physics’ enables our pragmatic engagement with the physical world and forms a key component of ‘common sense’ aspects of thought. Current artificial intelligence systems pale in their understanding of intuitive physics, in compa…
View article: HCMD-zero: Learning Value Aligned Mechanisms from Data
HCMD-zero: Learning Value Aligned Mechanisms from Data Open
Artificial learning agents are mediating a larger and larger number of interactions among humans, firms, and organizations, and the intersection between mechanism design and machine learning has been heavily investigated in recent years. H…
View article: Human-centered mechanism design with Democratic AI
Human-centered mechanism design with Democratic AI Open
Building artificial intelligence (AI) that aligns with human values is an unsolved problem. Here, we developed a human-in-the-loop research pipeline called Democratic AI, in which reinforcement learning is used to design a social mechanism…
View article: Probing Physics Knowledge Using Tools from Developmental Psychology
Probing Physics Knowledge Using Tools from Developmental Psychology Open
In order to build agents with a rich understanding of their environment, one key objective is to endow them with a grasp of intuitive physics; an ability to reason about three-dimensional objects, their dynamic interactions, and responses …
View article: Structure Learning in Motor Control:A Deep Reinforcement Learning Model
Structure Learning in Motor Control:A Deep Reinforcement Learning Model Open
Motor adaptation displays a structure-learning effect: adaptation to a new perturbation occurs more quickly when the subject has prior exposure to perturbations with related structure. Although this `learning-to-learn' effect is well docum…