Abstract: "We describe a heuristic search algorithm for generating optimal plans in a new class of decision problem, characterised by the incorporation of hidden state. The approach exploits the nature of the hidden state to reduce the state space by orders of magnitude. It then interleaves AO*-type heuristic expansion of the reduced space with forwards and backwards propagation phases to produce a solution in a fraction of the time required by other techniques. Results are provided on an outdoor path planning application.
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One...
Search-based planning is widely used for mobile robot motion planning because of its guarantees of o...
Many current state-of-the-art planners rely on forward heuristic search. The success of such search ...
Abstract. One of the most successful approaches in automated plan-ning is to use heuristic state-spa...
Potential heuristics, recently introduced by Pommerening et al., characterize admissible and consist...
This thesis explores limitations of heuristic search planning, and presents techniques to overcome t...
Heuristic search-based planners, such as HSP 2.0, solve STRIPS-style planning problems efficiently ...
Heuristic search is a successful approach to cost-optimal planning. Bidirectional heuristic search a...
Heuristic search has been widely applied to classical planning and has proven its efficiency in find...
We propose a heuristic search algorithm for finding optimal policies in a new class of sequential de...
Optimal heuristic searches such as A * search are widely used for planning but can rarely scale to l...
for a path from a starting state to the goal in a state space most typically modelled as a directed ...
In this dissertation a new heuristic planning system, which searches for plans in the space of the s...
This paper proposes and investigates a novel way of combining machine learning and heuristic search ...
The automatic derivation of heuristic functions for guiding the search for plans in large spaces is ...
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One...
Search-based planning is widely used for mobile robot motion planning because of its guarantees of o...
Many current state-of-the-art planners rely on forward heuristic search. The success of such search ...
Abstract. One of the most successful approaches in automated plan-ning is to use heuristic state-spa...
Potential heuristics, recently introduced by Pommerening et al., characterize admissible and consist...
This thesis explores limitations of heuristic search planning, and presents techniques to overcome t...
Heuristic search-based planners, such as HSP 2.0, solve STRIPS-style planning problems efficiently ...
Heuristic search is a successful approach to cost-optimal planning. Bidirectional heuristic search a...
Heuristic search has been widely applied to classical planning and has proven its efficiency in find...
We propose a heuristic search algorithm for finding optimal policies in a new class of sequential de...
Optimal heuristic searches such as A * search are widely used for planning but can rarely scale to l...
for a path from a starting state to the goal in a state space most typically modelled as a directed ...
In this dissertation a new heuristic planning system, which searches for plans in the space of the s...
This paper proposes and investigates a novel way of combining machine learning and heuristic search ...
The automatic derivation of heuristic functions for guiding the search for plans in large spaces is ...
It is well known that there cannot be a single "best" heuristic for optimal planning in general. One...
Search-based planning is widely used for mobile robot motion planning because of its guarantees of o...
Many current state-of-the-art planners rely on forward heuristic search. The success of such search ...