Computation of invariants, which are approximate reachability information for state-space search problems such as AI planning, has been considered to be more scalable when using a schematic representation of actions/events rather than an instantiated/ground representation. A disadvantage of schematic algorithms, however, is their complexity, which also leads to high runtimes when the number of schematic events/actions is high. We propose algorithms that reduce the problem of finding schematic invariants to solving a smaller ground problem.Peer reviewe
We explore methods for improving the performance of AI problem-solvers by automatically changing pro...
Previous research in Artificial Intelligence has identified the possibility of simplifying planning ...
Automated planning is the field of Artificial Intelligence (AI) that focuses on identifying sequence...
Computation of invariants, which are approximate reachability information for state-space search pro...
Abstract We continue to advocate a methodology that we used earlier for pattern discovery through ex...
AbstractThis paper is concerned with generalizing formal recognition methods from parsing theory to ...
We present a general algorithm for synthesizing state invari-ants that speed up automated planners a...
Due to the state-space explosion, many synthesis and verification problems for discrete event system...
AbstractAbstraction is a powerful technique for speeding up planning and search. A problem that can ...
Relaxed reachability analysis is relevant to efficient grounding, invariant synthesis as well as the...
Automation is becoming pervasive in everyday life, and many automated systems, such as unmanned aeri...
Relaxed reachability analysis is relevant to efficient grounding, invariant synthesis as well as the...
In this paperefficient computation of controllers in the context of Supervisory Control Theory (SCT)...
Our goal is to automatically generate heuristics to guide state space search. The heuristic values a...
The safety of infinite state systems can be checked by a backwardreachability procedure. For certain...
We explore methods for improving the performance of AI problem-solvers by automatically changing pro...
Previous research in Artificial Intelligence has identified the possibility of simplifying planning ...
Automated planning is the field of Artificial Intelligence (AI) that focuses on identifying sequence...
Computation of invariants, which are approximate reachability information for state-space search pro...
Abstract We continue to advocate a methodology that we used earlier for pattern discovery through ex...
AbstractThis paper is concerned with generalizing formal recognition methods from parsing theory to ...
We present a general algorithm for synthesizing state invari-ants that speed up automated planners a...
Due to the state-space explosion, many synthesis and verification problems for discrete event system...
AbstractAbstraction is a powerful technique for speeding up planning and search. A problem that can ...
Relaxed reachability analysis is relevant to efficient grounding, invariant synthesis as well as the...
Automation is becoming pervasive in everyday life, and many automated systems, such as unmanned aeri...
Relaxed reachability analysis is relevant to efficient grounding, invariant synthesis as well as the...
In this paperefficient computation of controllers in the context of Supervisory Control Theory (SCT)...
Our goal is to automatically generate heuristics to guide state space search. The heuristic values a...
The safety of infinite state systems can be checked by a backwardreachability procedure. For certain...
We explore methods for improving the performance of AI problem-solvers by automatically changing pro...
Previous research in Artificial Intelligence has identified the possibility of simplifying planning ...
Automated planning is the field of Artificial Intelligence (AI) that focuses on identifying sequence...