{"pk":29733,"title":"A Model of Fast Concept Inference with Object-Factorized Cognitive Programs","subtitle":null,"abstract":"The ability of humans to quickly identify general conceptsfrom a handful of images has proven difficult to emulate withrobots. Recently, a computer architecture was developed thatallows robots to mimic some aspects of this human ability bymodeling concepts as cognitive programs using an instructionset of primitive cognitive functions. This allowed a robot toemulate human imagination by simulating candidate programsin a world model before generalizing to the physical world.However, this model used a naive search algorithm that re-quired 30 minutes to discover a single concept, and becameintractable for programs with more than 20 instructions. Tocircumvents this bottleneck, we present an algorithm that emu-lates the human cognitive heuristics of object factorization andsub-goaling, allowing human-level inference speed, improvingaccuracy, and making the output more explainable.","language":"eng","license":{"name":"","short_name":"","text":null,"url":""},"keywords":[{"word":"zero-shot; cognitive programs; program induc-tion; concept inference; imitation learning"}],"section":"Poster Session 2","is_remote":true,"remote_url":"https://escholarship.org/uc/item/0zq2m13d","frozenauthors":[{"first_name":"Anonymous CogSci submission","middle_name":"","last_name":"","name_suffix":"","institution":"","department":""}],"date_submitted":null,"date_accepted":null,"date_published":"2020-01-01T18:00:00Z","render_galley":null,"galleys":[{"label":"PDF","type":"pdf","path":"https://journalpub.escholarship.org/cognitivesciencesociety/article/29733/galley/19590/download/"}]}