Paper Info
Title
Knowledge-Based Programs as Plans: Succinctness and the Complexity of Plan Existence.
Abstract
Knowledge-based programs (KBPs) are high-level protocols describing the course of action an agent should perform as a function of its knowledge. The use of KBPs for expressing action policies in AI planning has been surprisingly overlooked. Given that to each KBP corresponds an equivalent plan and vice versa, KBPs are typically more succinct than standard plans, but imply more on-line computation time. Here we make this argument formal, and prove that there exists an exponential succinctness gap between knowledge-based programs and standard plans. Then we address the complexity of plan existence. Some results trivially follow from results already known from the literature on planning under incomplete knowledge, but many were unknown so far.
Year
Venue
Field
2013
TARK
Incomplete knowledge,Course of action,Existential quantification,Succinctness,Computer science,Theoretical computer science,Artificial intelligence,Automated planning and scheduling,Machine learning
DocType
Volume
Citations 
Journal
abs/1310.6429
3
PageRank 
References 
Authors
0.41
3
2
Name
Order
Citations
PageRank
Jérôme Lang12838260.90
Bruno Zanuttini228925.43