We present a hierarchical planning system and its application to robotic manipulation. The
novel features of the system are: 1) it finds high-quality kinematic solutions to task-level …

We investigate the use of machine learning to create effective heuristics for search
algorithms such as IDA⁎ or heuristic-search planners such as FF. Our method aims to …

This volume presents novel computational models for representing digital humans and their
interactions with other virtual characters and meaningful environments. In this context, we …

Lately, several important advancements have been obtained in symbolic search. First,
bidirectional blind search has obtained good results on many domains. Second, perimeter …

We discuss the relationships between three approaches to greedy heuristic search: best-
first, hill-climbing, and beam search. We consider the design decisions within each family …

Informally, a set of abstractions of a state space S is additive if the distance between any two
states in S is always greater than or equal to the sum of the corresponding distances in the …

We consider the problem of computing a lightest derivation of a global structure using a set
of weighted rules. A large variety of inference problems in AI can be formulated in this …

This paper presents a real-time planning framework for multi-character navigation that
enables the use of multiple heterogeneous problem domains of differing complexities for …

Pattern databases are dictionaries for heuristic estimates storing state-to-goal distances in
state space abstractions. Their effectiveness is sensitive to the selection of the underlying …

A pattern database (PDB) is a heuristic function stored as a lookup table. This paper
considers how best to use a fixed amount (m units) of memory for storing pattern databases …