4 papers · 1 filter
Learning Admissible Heuristics via Cost Partitioning
Hugo Barral, Quentin Cappart, Marie-José Huguet +1
Admissible heuristics are essential for optimal planning, yet learning them remains challenging due to the risk of overestimation. Cost partitioning combines multiple abstraction h…
AI Planning: A Primer and Survey (Preliminary Report)
Dillon Z. Chen, Pulkit Verma, Siddharth Srivastava +2
Automated decision-making is a fundamental topic that spans multiple sub-disciplines in AI: reinforcement learning (RL), AI planning (AP), foundation models, and operations researc…
Graph Learning for Planning: The Story Thus Far and Open Challenges
Dillon Z. Chen, Mingyu Hao, Sylvie Thiébaux +1
Graph learning is naturally well suited for use in planning due to its ability to exploit relational structures exhibited in planning domains and to take as input planning instance…
Graph Learning for Numeric Planning
Dillon Z. Chen, Sylvie Thiébaux
Graph learning is naturally well suited for use in symbolic, object-centric planning due to its ability to exploit relational structures exhibited in planning domains and to take a…