Search Results for author:
Found 10 papers, 4 papers with code
Synthesis of Procedural Models for Deterministic Transition Systems
The combinatorial search is guided with functions that asses the complexity of the candidate programs, as well as their fitness to the given input set of examples.
Generalized Planning as Heuristic Search: A new planning search-space that leverages pointers over objects
First, the paper introduces a new pointer-based solution space for GP that is independent of the number of classical planning instances in a GP problem and the size of those instances (i. e. the number of objects, state variables and their domain sizes).
Representation and Synthesis of C++ Programs for Generalized Planning
The paper introduces a novel representation for Generalized Planning (GP) problems, and their solutions, as C++ programs.
Computing Programs for Generalized Planning as Heuristic Search
This paper adapts the planning as heuristic search paradigm to the particularities of GP, and presents the first native heuristic search approach to GP.
Scaling-up Generalized Planning as Heuristic Search with Landmarks
In this paper we define a landmark counting heuristic for GP (that considers sub-goal information that is not explicitly represented in the planning instances), and a novel heuristic search algorithm for GP (that we call PGP) and that progressively processes subsets of the planning instances of a GP problem.
Generalized Planning as Heuristic Search
First, the paper defines a novel GP solution space that is independent of the number of planning instances in a GP problem, and the size of these instances.
Generalized Planning with Positive and Negative Examples
Generalized planning aims at computing an algorithm-like structure (generalized plan) that solves a set of multiple planning instances.
Hierarchical Finite State Controllers for Generalized Planning
We show that hierarchical FSCs can represent generalized plans more compactly than individual FSCs.
Generalized Planning With Procedural Domain Control Knowledge
Generalized planning is the task of generating a single solution that is valid for a set of planning problems.
Learning STRIPS Action Models with Classical Planning
This paper presents a novel approach for learning STRIPS action models from examples that compiles this inductive learning task into a classical planning task.
