arXiv:2206.06530 공식 코드 · Papers with Code

MACQ: A Holistic View of Model Acquisition Techniques

Ethan Callanan, Rebecca De Venezia, Victoria Armstrong, Alison Paredes, Tathagata Chakraborti, Christian Muise

제출 2022-06-14

원문 초록

For over three decades, the planning community has explored countless methods for data-driven model acquisition. These range in sophistication (e.g., simple set operations to full-blown reformulations), methodology (e.g., logic-based vs. planing-based), and assumptions (e.g., fully vs. partially observable). With no fewer than 43 publications in the space, it can be overwhelming to understand what approach could or should be applied in a new setting. We present a holistic characterization of the action model acquisition space and further introduce a unifying framework for automated action model acquisition. We have re-implemented some of the landmark approaches in the area, and our characterization of all the techniques offers deep insight into the research opportunities that remain; i.e., those settings where no technique is capable of solving.

함께 살펴볼 논문

공통 태그를 근거로 연결했습니다. 실제 인용 관계나 논문의 우수성을 뜻하지 않습니다.

arXiv:2507.10539공통 태그 model공식 코드 · Papers with Code

Graph World Model

토론

이 논문과 연결된 포럼 글이 아직 없습니다.