This technical report presents DD* Lite, an efficient incremental search algorithm for problems that can capitalize on state dominance. Dominance relationships between nodes are used to prune graphs in search algorithms. Thus, exploiting state dominance relationships can considerably speed up search problems in large state spaces, such as mobile robot path planning considering uncertainty, time, or energy constraints. Incremental search techniques are useful when changes can occur in the search graph, such as when re-planning paths for mobile robots in partially known environments. While algorithms such as D* and D* Lite are very efficient incremental search algorithms, they cannot be applied as formulated to search problems in which state ...
This paper proposes incremental preference elicitation methods for multiobjective state space search...
In classical planning as search, duplicate state pruning is a standard method to avoid unnecessarily...
Incremental heuristic search methods can often replan paths much faster than incremental or heurist...
This paper presents DD * Lite, an efficient incremental search algorithm for problems that can capit...
This technical report presents DD * Lite, an efficient incremental search algorithm for problems tha...
Incremental search methods reuse information from previous searches to find solutions to a series of...
Incremental search algorithms, such as D* Lite, reuse information from previous searches to speed up...
Incremental heuristic searches try to reuse their previous search efforts whenever these are availab...
for a path from a starting state to the goal in a state space most typically modelled as a directed ...
Incremental search techniques find optimal solutions to series of similar search tasks much faster t...
Incremental search algorithms, such as Generalized Fringe-Retrieving A * and D * Lite, reuse search ...
© 2014, The Author(s). Situated agents frequently need to solve search problems in partially known t...
Path planning is a crucial issue in unknown environments where an autonomous mobile agent has to rea...
Abstract — For solving problems of robot navigation over unknown and changing terrain, many algorith...
Path planning is often a high-dimensional computationally-expensive planning problem as it requires ...
This paper proposes incremental preference elicitation methods for multiobjective state space search...
In classical planning as search, duplicate state pruning is a standard method to avoid unnecessarily...
Incremental heuristic search methods can often replan paths much faster than incremental or heurist...
This paper presents DD * Lite, an efficient incremental search algorithm for problems that can capit...
This technical report presents DD * Lite, an efficient incremental search algorithm for problems tha...
Incremental search methods reuse information from previous searches to find solutions to a series of...
Incremental search algorithms, such as D* Lite, reuse information from previous searches to speed up...
Incremental heuristic searches try to reuse their previous search efforts whenever these are availab...
for a path from a starting state to the goal in a state space most typically modelled as a directed ...
Incremental search techniques find optimal solutions to series of similar search tasks much faster t...
Incremental search algorithms, such as Generalized Fringe-Retrieving A * and D * Lite, reuse search ...
© 2014, The Author(s). Situated agents frequently need to solve search problems in partially known t...
Path planning is a crucial issue in unknown environments where an autonomous mobile agent has to rea...
Abstract — For solving problems of robot navigation over unknown and changing terrain, many algorith...
Path planning is often a high-dimensional computationally-expensive planning problem as it requires ...
This paper proposes incremental preference elicitation methods for multiobjective state space search...
In classical planning as search, duplicate state pruning is a standard method to avoid unnecessarily...
Incremental heuristic search methods can often replan paths much faster than incremental or heurist...