Improved Safe Real-time Heuristic Search
This work addresses real-time search challenges in domains with dead-ends, but it is incremental as it builds directly on SafeRTS.
The paper tackles the problem of dead-ends in real-time planning by improving the SafeRTS algorithm, which uses a safety predicate to maintain backup plans; experimental results confirm the new framework performs at least as well as SafeRTS.
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.