Planning has been one of the main research areas in AI. For about three decades AI researchers explore alternative paths to build intelligent agents with advanced planning capabilities. However, the classical AI planning techniques suffer from inapplicability to real world domains, due to several assumptions adopted to facilitate research. Attempts to apply planning into real domains must address the problem of uncertainty, which requires a revision of the classical planning framework. Probabilistic models seem to offer a promising alternative, providing models of planning where plans can be represented, generated and evaluated under a standard probabilistic interpretation of uncertainty. This survey paper 1 attempts to cover the recent wo...
A major reason for the success of the STRIPS planner and its derivatives was the use of a representa...
As the limitations of traditional AI plan representations have become apparent, researchers have tur...
Automated Planning is the component of Artificial Intelligence that studies the computational proces...
Our research area is planning under uncertainty, that is, making sequences of decisions in the face ...
Automated planning is a major topic of research in artificial intelligence, and enjoys a long and di...
Planning has made significant progress since its inception in the 1970s, in terms both of the effici...
AbstractIn this paper we discuss a class of tasks in which to study planning under uncertainty. We a...
Abstract. This paper proposes an unifying formulation for nondeter-ministic and probabilistic planni...
AbstractWe define the probabilistic planning problem in terms of a probability distribution over ini...
One reason for the success of the STRIPS planner and its derivatives was the use of a representation...
AbstractUncertainty, inherent in most real-world domains, can cause failure of apparently sound clas...
<p>Planning is an essential part of intelligent behavior and a ubiquitous task for both humans and r...
This report is a compendium of the extended abstracts submitted by participants at the 1990 AAAI Spr...
Attempts to apply classical planning techniques to realistic environments have met with two major d...
In this dissertation, we investigate two basic planning problems in Operations Research, non-probabi...
A major reason for the success of the STRIPS planner and its derivatives was the use of a representa...
As the limitations of traditional AI plan representations have become apparent, researchers have tur...
Automated Planning is the component of Artificial Intelligence that studies the computational proces...
Our research area is planning under uncertainty, that is, making sequences of decisions in the face ...
Automated planning is a major topic of research in artificial intelligence, and enjoys a long and di...
Planning has made significant progress since its inception in the 1970s, in terms both of the effici...
AbstractIn this paper we discuss a class of tasks in which to study planning under uncertainty. We a...
Abstract. This paper proposes an unifying formulation for nondeter-ministic and probabilistic planni...
AbstractWe define the probabilistic planning problem in terms of a probability distribution over ini...
One reason for the success of the STRIPS planner and its derivatives was the use of a representation...
AbstractUncertainty, inherent in most real-world domains, can cause failure of apparently sound clas...
<p>Planning is an essential part of intelligent behavior and a ubiquitous task for both humans and r...
This report is a compendium of the extended abstracts submitted by participants at the 1990 AAAI Spr...
Attempts to apply classical planning techniques to realistic environments have met with two major d...
In this dissertation, we investigate two basic planning problems in Operations Research, non-probabi...
A major reason for the success of the STRIPS planner and its derivatives was the use of a representa...
As the limitations of traditional AI plan representations have become apparent, researchers have tur...
Automated Planning is the component of Artificial Intelligence that studies the computational proces...