English (United Kingdom)

https://curated-unify.zendy.io/wp-json/zendy-region/v1/featured_content/oa?rat=en

https://curated-unify.zendy.io/wp-json/zendy-region/v1/highlighted_journal/

Global: Zendy Tools annual

Presents the keyphrase highlighting as premium feature

Keyphrase Highlighting

Presents the summarisation as premium feature

Summarisation

Insights

Presents the pdf analysis as premium feature

PDF Analysis

Presents the zaia usage as premium feature

ZAIA

Global: Zendy Tools monthly

Global: Zendy Plus monthly

Presents the access of premium content as premium feature

Premium Content

Global: Zendy Plus annual

Global: Zendy Free Plan

Many animals, and an increasing number of artificial agents, displaysophisticated capabilities to perceive and manipulate objects. But human beingsremain distinctive in their capacity for flexible, creative tool use -- usingobjects in new ways to act on the world, achieve a goal, or solve a problem. Tostudy this type of general physical problem solving, we introduce the VirtualTools game. In this game, people solve a large range of challenging physicalpuzzles in just a handful of attempts. We propose that the flexibility of humanphysical problem solving rests on an ability to imagine the effects ofhypothesized actions, while the efficiency of human search arises from richaction priors which are updated via observations of the world. We instantiatethese components in the "Sample, Simulate, Update" (SSUP) model and show thatit captures human performance across 30 levels of the Virtual Tools game. Morebroadly, this model provides a mechanism for explaining how people condensegeneral physical knowledge into actionable, task-specific plans to achieveflexible and efficient physical problem-solving.

Rapid trial-and-error learning with simulation supports flexible tool use and physical reasoning