• Corpus ID: 9537559

An Empirical Analysis of Some Heuristic Features for Local Search in LPG

  title={An Empirical Analysis of Some Heuristic Features for Local Search in LPG},
  author={Alfonso Gerevini and Alessandro Saetti and Ivan Serina},
LPG is a planner that performed very well in the last International planning competition (2002). The system is based on a stochastic local search procedure, and it incorporates several heuristic features. In this paper we experimentally analyze the most important of them with the goal of understanding and evaluating their impact on the performance of the planner. In particular, we examine three heuristic functions for evaluating the search neighborhood and some settings of the "noise" parameter… 

Figures and Tables from this paper

An Empirical Analysis of Some Heuristic Features for Planning through Local Search and Action Graphs
Experimental results indicate that the current version of LPG using the identified best heuristic techniques as the default settings is competitive with the winner of the last (2008) International Planning Competition.
On the Use of Landmarks in LPG
This work proposes the use of Landmarks for the LPG planner, considering different design choices and analysing empirically its impact on the performance of the planner, finding results comparable with the state-of-the-art planner LAMA.
LPG-TD : a Fully Automated Planner for PDDL 2 . 2 Domains
Like the previous version of LPG, the new version is based on a stochastic local search in the space of particular “action graphs” derived from the planning problem specification. In LPG-TD, this
Planning with Derived Predicates through Rule-Action Graphs and Relaxed-Plan Heuristics
This work proposes an approach to planning with derived predicates where the search space consists of particular graphs of actions and rules, called rule-action graphs, representing partial plans, and presents some techniques for managing domain rules in the context of a local search process for rule- action graphs.
Statement of research interest
An analysis of the IPC-4 results show that the planner performs very well compared to other recent temporal planners supporting deterministic exogenous events and derived predicates, both in terms of CPU-time required to find a plan and quality of the best plans that can be generated by the system.
An Approach to Temporal Planning and Scheduling in Domains with Predictable Exogenous Events
This paper proposes an approach to planning in temporal domains with exogenous events that happen at known times, imposing the constraint that certain actions in the plan must be executed during some predefined time windows which integrates constraint-based temporal reasoning into a graph-based planning framework using local search.
SGPlan: Subgoal Partitioning and Resolution in Planning
Methods for the detection of reasonable orders among subgoals, an intermediate goalagenda analysis to hierarchically decompose each subproblem, a search-space-reduction algorithm to eliminate irrelevant actions in subproblems, and a strategy to call the best planner to solve each bottom-level subproblem are developed.
An Interactive Tool for Plan Generation, Inspection, and Visualization
The tool provides an environment through which the user can interact with a state-of-the-art domain-independent planner, and obtain an effective visualization of a rich variety of information during planning, including the reasons why an action is being planned or why its execution in the current plan is expected to fail.


Local Search Topology in Planning Benchmarks: An Empirical Analysis
Looking at a collection of planning benchmarks, the results suggest that, given the heuristic based on the relaxation, many planning benchmarks are simple in structure, shedding light on the recent success of heuristic planners employing local search.
The FF Planning System: Fast Plan Generation Through Heuristic Search
A novel search strategy is introduced that combines hill-climbing with systematic search, and it is shown how other powerful heuristic information can be extracted and used to prune the search space.
Accelerating Partial-Order Planners: Some Techniques for Effective Search Control and Pruning
Improved plan and goal selection strategies and the use of operator parameter domains to prune search gave speedups by an order of magnitude or more for difficult problems, both with the default ucpop search strategy and with the improved strategy.
Planning Through Stochastic Local Search and Temporal Action Graphs in LPG
This paper focuses on temporal planning, introducing TA-graphs and proposing some techniques to guide the search in LPG using this representation, and shows that these techniques can be very effective.
Fast Planning through Greedy Action Graphs
This paper proposes a new search method in the context of Blum and Furst's planning graph approach, which is based on local search, and introduces three heuristics to guide the local search.
Sapa: A Scalable Multi-objective Heuristic Metric Temporal Planner
The technical details of extracting the heuristics are described and an empirical evaluation of the current implementation of Sapa is presented, one of the best domain independent planners for domains with metric and temporal constraints in the third International Planning Competition.
Sapa: A Multi-objective Metric Temporal Planner
An implementation of SAPA using many of the techniques presented in this paper was one of the best domain independent planners for domains with metric and temporal constraints in the third International Planning Competition, held at AIPS-02.
The 3rd International Planning Competition: Results and Analysis
The paper addresses the questions of comparative performance between planners, comparative difficulty of domains, the degree of agreement between planners about the relative difficulty of individual problem instances and the question of how well planners scale relative to one another over increasingly difficult problems through statistical analysis of the raw results.
Fast Planning Through Planning Graph Analysis
Noise Strategies for Improving Local Search
It is shown that mixed random walk is the superior strategy for solving MAX-SAT problems, and results demonstrating the effectiveness of local search with walk for solving circuit synthesis and circuit diagnosis problems are presented.