scholarly journals The GRT Planning System: Backward Heuristic Construction in Forward State-Space Planning

2001 ◽  
Vol 15 ◽  
pp. 115-161 ◽  
Author(s):  
I. Refanidis ◽  
I. Vlahavas
Keyword(s):  
State Space ◽  
Intermediate State ◽  
Forward Direction ◽  
Planning System ◽  
Search Process ◽  
Space Planning ◽  
Two Phases ◽  
Performance Results ◽  
Domain Independent ◽  
State Space Planning

This paper presents GRT, a domain-independent heuristic planning system for STRIPS worlds. GRT solves problems in two phases. In the pre-processing phase, it estimates the distance between each fact and the goals of the problem, in a backward direction. Then, in the search phase, these estimates are used in order to further estimate the distance between each intermediate state and the goals, guiding so the search process in a forward direction and on a best-first basis. The paper presents the benefits from the adoption of opposite directions between the preprocessing and the search phases, discusses some difficulties that arise in the pre-processing phase and introduces techniques to cope with them. Moreover, it presents several methods of improving the efficiency of the heuristic, by enriching the representation and by reducing the size of the problem. Finally, a method of overcoming local optimal states, based on domain axioms, is proposed. According to it, difficult problems are decomposed into easier sub-problems that have to be solved sequentially. The performance results from various domains, including those of the recent planning competitions, show that GRT is among the fastest planners.

Improving Domain-Independent Heuristic State-Space Planning via plan cost predictions

2021 ◽  
pp. 1-27
Author(s):  
Francesco Percassi ◽  
Alfonso E. Gerevini ◽  
Enrico Scala ◽  
Ivan Serina ◽  
Mauro Vallati
Keyword(s):  
State Space ◽  
Space Planning ◽  
Domain Independent ◽  
State Space Planning

scholarly journals Multiobjective heuristic state-space planning

2003 ◽  
Vol 145 (1-2) ◽  
pp. 1-32 ◽  
Author(s):  
Ioannis Refanidis ◽  
Ioannis Vlahavas
Keyword(s):  
State Space ◽  
Space Planning ◽  
State Space Planning

State-Space Planning

2004 ◽  
pp. 69-83 ◽  
Author(s):  
Malik Ghallab ◽  
Dana Nau ◽  
Paolo Traverso
Keyword(s):  
State Space ◽  
Space Planning ◽  
State Space Planning

STATE-SPACE PLANNING WITH VARIANTS OF A*

2006 ◽  
Vol 15 (03) ◽  
pp. 433-464 ◽  
Author(s):  
AMOL DATTATRAYA MALI ◽  
MINH TANG
Keyword(s):  
State Space ◽  
Heuristic Search ◽  
Empirical Evaluation ◽  
Heuristic Evaluation ◽  
Lazy Evaluation ◽  
Two Phase ◽  
Space Planning ◽  
Future Work ◽  
Phase Evaluation ◽  
Domain Independent

Significant advances have occurred in heuristic search for planning in the last eleven years. Many of these planners use A*-style search. We report on five sound and complete domain-independent forward state-space STRIPS planners in this paper. The planners are AWA* (Adjusted Weighted A*), MAWA* (Modified AWA*), AWA*-AC (AWA* with action conflict-based adjustment), AWA*-PD (AWA* with deleted preconditions-based adjustment), and AWA*-AC-LE (AWA*-AC with lazy evaluation). AWA* is the first planner to use node-dependent weighting in A*. MAWA*, AWA*-AC, AWA*-PD, and AWA*-AC-LE use conditional two-phase heuristic evaluation. MAWA* applies node-dependent weighting to a subset of the nodes in the fringe, after the two-phase evaluation. One novel idea in AWA*-AC-LE is lazy heuristic evaluation which does not construct relaxed plans to compute heuristic values for all nodes. We report on an empirical comparison of AWA*, MAWA*, AWA*-AC, AWA*-PD, and AWA*-AC-LE with classical planners AltAlt, FF, HSP-2 and STAN 4. Our variants of A* outperform these planners on several problems. The empirical evaluation shows that heuristic search planning is significantly benefitted by node-dependent weighting, conditional two-phase heuristic evaluation and lazy evaluation. We report on the insights about inferior performance of our planners in some domains using the notion of waiting time. We discuss many other variants of A*, state-space planners and directions for future work.

scholarly journals Potential for the use of information systems in the management of construction waste

2018 ◽  
Vol 196 ◽  
pp. 04081 ◽  
Author(s):  
Aleksandr Aleksanin
Keyword(s):  
Information Systems ◽  
Information Technologies ◽  
Information Modeling ◽  
Planning System ◽  
Design Stage ◽  
Resource Saving ◽  
Construction Waste ◽  
Space Planning ◽  
Planning Decisions ◽  
Building Information

At the present stage of the development of the construction industry, based on the principles of sustainable development, special attention should be paid to the formation of construction waste. Reserves for improving the level of efficiency of waste management can be found in the application of modern information technologies and their adaptation to resource-saving problems. The use of information systems is advisable at all stages of the life cycle of a building. Today, the technology of building information modeling (BIM) is actively developing, which can significantly reduce the amount of waste generation in construction. This is possible with its implementation at the design stage, in order to avoid irrational design decisions, collisions, etc. Information systems for data transmission allow rapid exchange of information between project participants, promptly warn about changes in space-planning decisions, materials, structures and equipment. At the stage of operation, in the presence of the information model of the building, it is possible to create a planning system for the organization of works of major overhaul or reconstruction. This article also proposes a description of the functions that an information system must have aimed at coordinating the management of construction waste in the region.

Heuristics for Domain-Independent Planning: A Survey

2011 ◽  
Vol 135-136 ◽  
pp. 573-577 ◽  
Author(s):  
Rui Shi Liang ◽  
Min Huang
Keyword(s):  
State Space ◽  
Heuristic Search ◽  
Research Work ◽  
Future Research ◽  
Survey Analysis ◽  
Work Related ◽  
State Space Search ◽  
Survey Results ◽  
Domain Independent ◽  
Intense Research

Increasing interest has been devoted to Planning as Heuristic Search over the years. Intense research has focused on deriving fast and accurate heuristics for domain-independent planning. This paper reports on an extensive survey and analysis of research work related to heuristic derivation techniques for state space search. Survey results reveal that heuristic techniques have been extensively applied in many efficient planners and result in impressive performances. We extend the survey analysis to suggest promising avenues for future research in heuristic derivation and heuristic search techniques.

scholarly journals HDDL: An Extension to PDDL for Expressing Hierarchical Planning Problems

2020 ◽  
Vol 34 (06) ◽  
pp. 9883-9891 ◽  
Author(s):  
Daniel Höller ◽  
Gregor Behnke ◽  
Pascal Bercher ◽  
Susanne Biundo ◽  
Humbert Fiorino ◽  
...  
Keyword(s):  
Planning System ◽  
Hierarchical Planning ◽  
Planning Systems ◽  
Description Language ◽  
Input Language ◽  
Common Input ◽  
Modeling Process ◽  
Planning Problems ◽  
Domain Independent ◽  
Tailored Advice

The research in hierarchical planning has made considerable progress in the last few years. Many recent systems do not rely on hand-tailored advice anymore to find solutions, but are supposed to be domain-independent systems that come with sophisticated solving techniques. In principle, this development would make the comparison between systems easier (because the domains are not tailored to a single system anymore) and – much more important – also the integration into other systems, because the modeling process is less tedious (due to the lack of advice) and there is no (or less) commitment to a certain planning system the model is created for. However, these advantages are destroyed by the lack of a common input language and feature set supported by the different systems. In this paper, we propose an extension to PDDL, the description language used in non-hierarchical planning, to the needs of hierarchical planning systems.

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