Add to ORKGA planning system must reason about the uncertainty of continuous variables in order to accurately project the possible system state over time. A method is devised for directly reasoning about the uncertainty in continuous activity duration and resource usage for planning problems. By representing random variables as parametric distributions, computing projected system state can be simplified. Common approximations and novel methods are compared for over-constrained and lightly constrained domains within an iterative repair planner. Results show improvements in robustness over the conventional non-probabilistic representation by reducing the number of constraint violations during execution. The improvement is more significant for larger pro...
Our research’s aim is to explore the use of constraint satisfaction techniques in probabilistic plan...
This paper presents a model-based planner called the Probabilistic Sulu Planner or the p-Sulu Planne...
Flexibility in agent scheduling increases the resilience of temporal plans in the face of new constr...
A planning system must reason about the uncertainty of continuous variables in order to accurately p...
We define the robustness of a sequential plan as the probability that it will execute successfully d...
A critical challenge in temporal planning is robustly dealing with non-determinism introduced by the...
When planning in uncertain domains, it can be of great benefit if the planner is aware of the nature...
A critical challenge in temporal planning is robustly dealing with non-determinism, e.g., the durati...
In temporally uncertain domains, taking uncertainty into account while planning leads to problems wi...
Reasoning about uncertainty is an essential component of many real-world plan-ning problems, such as...
This paper presents a model-based planner called the Probabilistic Sulu Planner or the p-Sulu Plann...
The main focus of our work is the use of classical planning algorithms in service of more complex pr...
AbstractUncertainty, inherent in most real-world domains, can cause failure of apparently sound clas...
When agents devise plans for execution in the real world, they face two forms of uncertainty " ...
AbstractWe define the probabilistic planning problem in terms of a probability distribution over ini...
Our research’s aim is to explore the use of constraint satisfaction techniques in probabilistic plan...
This paper presents a model-based planner called the Probabilistic Sulu Planner or the p-Sulu Planne...
Flexibility in agent scheduling increases the resilience of temporal plans in the face of new constr...
A planning system must reason about the uncertainty of continuous variables in order to accurately p...
We define the robustness of a sequential plan as the probability that it will execute successfully d...
A critical challenge in temporal planning is robustly dealing with non-determinism introduced by the...
When planning in uncertain domains, it can be of great benefit if the planner is aware of the nature...
A critical challenge in temporal planning is robustly dealing with non-determinism, e.g., the durati...
In temporally uncertain domains, taking uncertainty into account while planning leads to problems wi...
Reasoning about uncertainty is an essential component of many real-world plan-ning problems, such as...
This paper presents a model-based planner called the Probabilistic Sulu Planner or the p-Sulu Plann...
The main focus of our work is the use of classical planning algorithms in service of more complex pr...
AbstractUncertainty, inherent in most real-world domains, can cause failure of apparently sound clas...
When agents devise plans for execution in the real world, they face two forms of uncertainty " ...
AbstractWe define the probabilistic planning problem in terms of a probability distribution over ini...
Our research’s aim is to explore the use of constraint satisfaction techniques in probabilistic plan...
This paper presents a model-based planner called the Probabilistic Sulu Planner or the p-Sulu Planne...
Flexibility in agent scheduling increases the resilience of temporal plans in the face of new constr...