Sapa is a domain-independent heuristic forward chaining planner that can handle durative actions, metric resource constraints, and deadline goals. It is designed to be capable of handling the multi-objective nature of metric temporal planning. Our technical contributions include (i) planning-graph based methods for deriving heuristics that are sensitive to both cost and makespan (ii) techniques for adjusting the heuristic estimates to take action interactions and metric resource limitations into account and (iii) a linear time greedy post-processing technique to improve execution flexibility of the solution plans. An implementation of Sapa using many of the techniques presented in this paper was one of the best domain independent planners f...
Temporal planning offers numerous advantages when based on an expressive representation. Timelines h...
Recently tremendous advances have been made in the performance of AI planning systems. However incre...
Recently, the areas of planning and scheduling in artificial intelligence (AI) have witnessed a big ...
Sapa is a domain-independent heuristic forward chaining planner that can handle durative ac-tions, m...
Sapa is a domain-independent heuristic forward chaining planner that can handle durative ac-tions, m...
Most of current works on planning community assume the completeness of the physical dynamics or the ...
In this paper we address the problem of post-processing posi-tion constrained plans, output by many ...
Planning for and controlling a network of interacting devices requires a planner that accounts for t...
Temporal logics have been used in autonomous planning to represent and reason about temporal plannin...
Recent advances in constraint satisfaction and heuristic search have made it possible to solve class...
A key feature of modern optimal planners such as graphplan and blackbox is their ability to prune la...
Many planning domains have to deal with temporal features that can be expressed using durations that...
The last eight years have seen dramatic progress in tempo-ral planning as highlighted by the tempora...
The main objective of my research activity is the develop-ment and the experimental analysis of effi...
Recently tremendous advances have been made in the performance of AI planning systems. However incre...
Temporal planning offers numerous advantages when based on an expressive representation. Timelines h...
Recently tremendous advances have been made in the performance of AI planning systems. However incre...
Recently, the areas of planning and scheduling in artificial intelligence (AI) have witnessed a big ...
Sapa is a domain-independent heuristic forward chaining planner that can handle durative ac-tions, m...
Sapa is a domain-independent heuristic forward chaining planner that can handle durative ac-tions, m...
Most of current works on planning community assume the completeness of the physical dynamics or the ...
In this paper we address the problem of post-processing posi-tion constrained plans, output by many ...
Planning for and controlling a network of interacting devices requires a planner that accounts for t...
Temporal logics have been used in autonomous planning to represent and reason about temporal plannin...
Recent advances in constraint satisfaction and heuristic search have made it possible to solve class...
A key feature of modern optimal planners such as graphplan and blackbox is their ability to prune la...
Many planning domains have to deal with temporal features that can be expressed using durations that...
The last eight years have seen dramatic progress in tempo-ral planning as highlighted by the tempora...
The main objective of my research activity is the develop-ment and the experimental analysis of effi...
Recently tremendous advances have been made in the performance of AI planning systems. However incre...
Temporal planning offers numerous advantages when based on an expressive representation. Timelines h...
Recently tremendous advances have been made in the performance of AI planning systems. However incre...
Recently, the areas of planning and scheduling in artificial intelligence (AI) have witnessed a big ...