Planning with concurrent durative actions and probabilistic effects, or probabilistic temporal planning, is a relatively new area of research. The challenge is to replicate the success of modern temporal and probabilistic planners with domains that exhibit an interaction between time and uncertainty. We present a general framework for probabilistic temporal planning in which effects, the time at which they occur, and action durations are all probabilistic. This framework includes a search space that is designed for solving probabilistic temporal planning problems via heuristic search, an algorithm that has been tailored to work with it, and an effective heuristic based on an extension of the planning graph data structure. Prottle is a plann...
Many planning domains have to deal with temporal features that can be expressed using durations that...
AbstractThis paper integrates logical and probabilistic approaches to the representation of planning...
The Graphplan planner has enjoyed considerable success as a planning algorithm for classical STRIPS ...
Planning with concurrent durative actions and probabilistic effects, or probabilistic temporal plann...
Few temporal planners handle both concurrency and uncer-tain durations, but these features commonly ...
We consider the problem of planning optimally in potentially concurrent probabilistic domains: actio...
We consider the problem of planning optimally in potentially concurrent probabilistic domains: actio...
Probabilistic planning problems are often modeled as Markov decision problems (MDPs), which assume t...
The treatment of exogenous events in planning is practically important in many real-world domains wh...
The treatment of exogenous events in planning is practically important in many realworld domains whe...
An interesting class of planning domains, including planning for daily activities of Mars rovers, in...
We present an any-time concurrent probabilistic tempo-ral planner that includes continuous and discr...
In Temporal Planning a typical assumption is that the agent controls the execution time of all event...
Temporal projection, defined as the prediction of what might happen when a plan is executed, is an i...
Many planning domains have temporal features that can be expressed using durations associated with a...
Many planning domains have to deal with temporal features that can be expressed using durations that...
AbstractThis paper integrates logical and probabilistic approaches to the representation of planning...
The Graphplan planner has enjoyed considerable success as a planning algorithm for classical STRIPS ...
Planning with concurrent durative actions and probabilistic effects, or probabilistic temporal plann...
Few temporal planners handle both concurrency and uncer-tain durations, but these features commonly ...
We consider the problem of planning optimally in potentially concurrent probabilistic domains: actio...
We consider the problem of planning optimally in potentially concurrent probabilistic domains: actio...
Probabilistic planning problems are often modeled as Markov decision problems (MDPs), which assume t...
The treatment of exogenous events in planning is practically important in many real-world domains wh...
The treatment of exogenous events in planning is practically important in many realworld domains whe...
An interesting class of planning domains, including planning for daily activities of Mars rovers, in...
We present an any-time concurrent probabilistic tempo-ral planner that includes continuous and discr...
In Temporal Planning a typical assumption is that the agent controls the execution time of all event...
Temporal projection, defined as the prediction of what might happen when a plan is executed, is an i...
Many planning domains have temporal features that can be expressed using durations associated with a...
Many planning domains have to deal with temporal features that can be expressed using durations that...
AbstractThis paper integrates logical and probabilistic approaches to the representation of planning...
The Graphplan planner has enjoyed considerable success as a planning algorithm for classical STRIPS ...