In this paper we present a planner, LPRPG-P, capable of reasoning with the non-temporal subset of PDDL 3 preferences. Our focus is on computation of relaxed plan based heuristics that effectively guide a planner towards good solutions satisfying preferences. We build on the planner LPRPG, a hybrid relaxed planning graph (RPG)--linear programming (LP) approach. We make extensions to the RPG to reason with propositional preferences, and to the LP to reason with numeric preferences. LPRPG-P is the first planner with direct guidance for numeric preference satisfaction, exploiting the strong numeric reasoning of the LP. We introduce an anytime search approach for use with our new heuristic, and present results showing that LPRPG-P extends t...
AbstractPlanning graphs have been shown to be a rich source of heuristic information for many kinds ...
The automatic derivation of heuristic functions for guiding the search for plans is a fundamental te...
The FF relaxed plan heuristic is one of the most effective techniques in domain-independent satisfic...
AbstractPlanning with preferences involves not only finding a plan that achieves the goal, it requir...
Abstract. We present a declarative language, PP, for the specification of preferences between possib...
Planning is one of the fundamental problems of artificial intelligence. A classic planning problem ...
Although reachability heuristics have been shown to be use-ful in conformant an contingent planning,...
Temporal planning methods usually focus on the objective of minimizing makespan. Unfortunately, this...
The availability of informed (but inadmissible) planning heuristics has enabled the development of h...
We present an algorithm that quickly finds optimal plans for unforeseen agent preferences within gra...
We present some techniques for planning in domains specified with the recent standard language pddl2...
AbstractWe present a heuristic search approach to solve partial satisfaction planning (PSP) problems...
AbstractIn this paper, we address the problem of specifying and computing preferred plans using rich...
The ParLPG planning system is based on the idea of us-ing a generic algorithm configuration procedur...
Recent advances in AI planning have centred upon the reduction of planning to a constraint satisfact...
AbstractPlanning graphs have been shown to be a rich source of heuristic information for many kinds ...
The automatic derivation of heuristic functions for guiding the search for plans is a fundamental te...
The FF relaxed plan heuristic is one of the most effective techniques in domain-independent satisfic...
AbstractPlanning with preferences involves not only finding a plan that achieves the goal, it requir...
Abstract. We present a declarative language, PP, for the specification of preferences between possib...
Planning is one of the fundamental problems of artificial intelligence. A classic planning problem ...
Although reachability heuristics have been shown to be use-ful in conformant an contingent planning,...
Temporal planning methods usually focus on the objective of minimizing makespan. Unfortunately, this...
The availability of informed (but inadmissible) planning heuristics has enabled the development of h...
We present an algorithm that quickly finds optimal plans for unforeseen agent preferences within gra...
We present some techniques for planning in domains specified with the recent standard language pddl2...
AbstractWe present a heuristic search approach to solve partial satisfaction planning (PSP) problems...
AbstractIn this paper, we address the problem of specifying and computing preferred plans using rich...
The ParLPG planning system is based on the idea of us-ing a generic algorithm configuration procedur...
Recent advances in AI planning have centred upon the reduction of planning to a constraint satisfact...
AbstractPlanning graphs have been shown to be a rich source of heuristic information for many kinds ...
The automatic derivation of heuristic functions for guiding the search for plans is a fundamental te...
The FF relaxed plan heuristic is one of the most effective techniques in domain-independent satisfic...