Delta Epsilon Alpha Star: A PAC-Admissible Search Algorithm

TL;DR

This paper introduces Delta Epsilon Alpha Star, a real-time robotic search algorithm that balances path optimality and probabilistic guarantees, and proposes PAC-admissibility as a new criterion for search algorithms.

Contribution

It presents a novel search algorithm with bounded deviation and introduces PAC-admissibility as a relaxed, more suitable criterion for robotic search tasks.

Findings

Delta Epsilon Alpha Star achieves a balanced search path with minimal backtracking.

PAC-admissibility outperforms epsilon-admissibility in robotic search scenarios.

The algorithm provides probabilistic bounds on path deviation.

Abstract

Delta Epsilon Alpha Star is a minimal coverage, real-time robotic search algorithm that yields a moderately aggressive search path with minimal backtracking. Search performance is bounded by a placing a combinatorial bound, epsilon and delta, on the maximum deviation from the theoretical shortest path and the probability at which further deviations can occur. Additionally, we formally define the notion of PAC-admissibility -- a relaxed admissibility criteria for algorithms, and show that PAC-admissible algorithms are better suited to robotic search situations than epsilon-admissible or strict algorithms.