Abstract: Generalized planning aims at finding a general solution for a set of similar planning
problems. Abstractions are widely used to solve such problems. The idea is to develop an abstract model of
the problem that suppresses less important details, find a solution in the abstract model, and use this
solution to guide the search for a solution in the concrete model. A popular kind of abstract models for
generalized planning is qualitative numerical planning (QNP) introduced by Srivastava et al. and shown to be
decidable: QNP is classical planning extended with non-negative real variables that can be increased or
decreased by some arbitrary amount. In this talk, I will introduce our recent work on a uniform abstraction
framework for generalized planning where we define and analyze the notions of sound and complete
abstractions, automatic verification of sound abstractions for generalized planning, a native QNP solver
based on AND/OR graph search, and a sound and complete abstraction method for generalized planning with
baggable objects.