Name
Abstract | ||
|---|---|---|
A fundamental concern in real-time planning is the presence of dead-ends in the state space, from which no goal is reachable. Recently, the SafeRTS algorithm was proposed for searching in such spaces. SafeRTS exploits a user-provided predicate to identify safe states, from which a goal is likely reachable, and attempts to maintain a backup plan for reaching a safe state at all times. In this paper, we study the SafeRTS approach, identify certain properties of its behavior, and design an improved framework for safe real-time search. We prove that the new approach performs at least as well as SafeRTS and present experimental results showing that its promise is fulfilled in practice. |
Year | Venue | Field |
|---|---|---|
2019 | SOCS | Heuristic,Computer science,Theoretical computer science,Exploit,Artificial intelligence,Predicate (grammar),State space,Machine learning,Backup |
DocType | Volume | Citations |
Journal | abs/1905.06402 | 0 |
PageRank | References | Authors |
0.34 | 0 | 3 |
Name | Order | Citations | PageRank |
|---|---|---|---|
| Bence Cserna | 1 | 1 | 3.76 |
| Kevin C. Gall | 2 | 0 | 0.34 |
| Wheeler Ruml | 3 | 1870 | 130.48 |