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Planning as satisfiability: Heuristics
2012
Artificial Intelligence
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as VSIDS, and often lifts it to the same level with other search methods such as explicit state-space search with heuristic search algorithms. ...
The strategy is based on generic principles about properties of plans, and its performance with standard planning benchmarks often substantially improves on generic variable selection heuristics, such ...
These conditions are satisfied by all main encodings of planning as SAT [23] . ...
doi:10.1016/j.artint.2012.08.001
fatcat:e75kvn6ncjavzooozno7j725su
SAS+ Planning as Satisfiability
2012
The Journal of Artificial Intelligence Research
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Planning as satisfiability is a principal approach to planning with many eminent advantages. The existing planning as satisfiability techniques usually use encodings compiled from STRIPS. ...
The new scheme exploits the structural information in SAS+, resulting in an encoding that is both more compact and efficient for planning. ...
Introduction Planning as satisfiability (SAT) is one of the main paradigms for planning. ...
doi:10.1613/jair.3442
fatcat:ug5taksm6bgk7nlsldt3q4ngm4
Introducing Preferences in Planning as Satisfiability
2010
Journal of Logic and Computation
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Planning as Satisfiability is one of the most well-known and effective techniques for classical planning: SATPLAN has been the winning system in the deterministic track for optimal planners in the 4th ...
In this paper we extend the Planning as Satisfiability approach in order to handle preferences and SATPLAN in order to solve problems with simple preferences. ...
In planning as satisfiability, plans for Π n are generated by invoking a SAT solver on Π n . ...
doi:10.1093/logcom/exq023
fatcat:fgojeq2rvbg3ve34jppgah72mi
Planning as heuristic search
2001
Artificial Intelligence
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Heuristic search planners like HSP transform planning problems into problems of heuristic search by automatically extracting heuristics from Strips encodings. ...
In the AIPS98 Planning Contest, the HSP planner showed that heuristic search planners can be competitive with state-of-the-art Graphplan and SAT planners. ...
It's simple to show that the resulting measures satisfy Eq. (1). ...
doi:10.1016/s0004-3702(01)00108-4
fatcat:cm6bir2gbfgxbdcbzqwyonvn5i
Planning as satisfiability: parallel plans and algorithms for plan search
2006
Artificial Intelligence
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Until now the application of ∃-step semantics in planning as satisfiability was hampered by the cubic size of the obvious encodings. ...
of a sequential plan with as many operators as in the parallel one. ...
PLANNING AS SATISFIABILITY Planning as satisfiability was introduced by Kautz and Selman [1992] . ...
doi:10.1016/j.artint.2006.08.002
fatcat:kmcw2fkh6vdfzggdqlny4a2dhu
μ-SATPLAN: Multi-agent planning as satisfiability
2012
Knowledge-Based Systems
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In this algorithm, agents use l-SATPLAN as the underlying planner for generating individual and joint consistent plans. ...
As the agents share the same environment, they need to find a coordinated course of action that avoids harmful (or negative) interactions, and benefit from positive interactions, whenever this is possible ...
The idea of distributed planning as SAT problem has also been discussed in [17] where the distributed planning problem is seen as the process of finding a satisfying assignment for both propositional ...
doi:10.1016/j.knosys.2011.07.019
fatcat:yuz5tuzqgvgx3hz7zm2mwsn7uu
Phase Selection Heuristics for Satisfiability Solvers
[article]
2011
arXiv
pre-print
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This can be seen as an improvement of the heuristic proposed by Jeroslow-Wang (1990). ...
We incorporate the ACE heuristic and the existing phase selection heuristics in the new solver MPhaseSAT, and select a phase heuristic in a way similar to portfolio methods. ...
Introduction Satisfiability (SAT) is a classic NP-complete problem, and has applications in numerous fields such as computer aided design, data diagnosis, EDA, logic reasoning, cryptanalysis, planning, ...
arXiv:1106.1372v1
fatcat:eamft4sv5bbwzk4lxtddxtscsa
HTN Planning as Heuristic Progression Search
2020
The Journal of Artificial Intelligence Research
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In this article, we propose the use of progression search as basis for heuristic HTN planning systems. ...
Then, we introduce a method to apply arbitrary classical planning heuristics to guide the search in HTN planning. ...
In this article, we propose the use of progression-based search as basis for heuristic HTN planning systems. ...
doi:10.1613/jair.1.11282
fatcat:5pw3r3ciwjhqtefm6lo4huyrd4
Exploiting Macro-actions and Predicting Plan Length in Planning as Satisfiability
[chapter]
2011
Lecture Notes in Computer Science
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Macro-actions are sequences of actions that typically occur in the solution plans, while a planning horizon of a problem is the length of a (possibly optimal) plan solving it. ...
In this work, we focus on the well-known SAT-based approach to planning and investigate two types of learned knowledge that have not been studied in this planning framework before: macro-actions and planning ...
In this paper, we consider two types of learned knowledge for optimal planners in the "planning as satisfiability" framework (also called SAT-based planning) [11] : macro-actions and the planning horizon ...
doi:10.1007/978-3-642-23954-0_19
fatcat:vfbz5f7h3venbfwf4f4qjdm2l4
Planning as satisfiability with IPC simple preferences and action costs
2012
AI Communications
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At the same time, as a side effect of this analysis, challenging Max-SAT and PB benchmarks have been identified, as well as the Max-SAT and PB solvers performing best on these planning problems. ...
Moreover, as we said before, the approach in [GM11] relies on an ordering of the heuristic that can hit performance, while the optimization solvers employed do not rely on such heuristics. ...
Even if they solve a different problem to us, the overall goal is the same as in our paper, i.e. to allow the planning as satisfiability approach to take into account plan quality issues other than the ...
doi:10.3233/aic-2012-0540
fatcat:7c7zcgz7ufazte7xwpn2b3vrqm
Reinforcement Learning for Classical Planning: Viewing Heuristics as Dense Reward Generators
[article]
2022
arXiv
pre-print
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These classical heuristics act as dense reward generators to alleviate the sparse-rewards issue and enable our RL agent to learn domain-specific value functions as residuals on these heuristics, making ...
We demonstrate on several classical planning domains that using classical heuristics for RL allows for good sample efficiency compared to sparse-reward RL. ...
Value Iteration for Classical Planning Our main approach will be to learn a value function that can be used as a heuristic to guide planning. ...
arXiv:2109.14830v2
fatcat:s4bxrobylzgpbdjdm4i4rggnnm
Deterministic Oversubscription Planning as Heuristic Search: Abstractions and Reformulations
2015
The Journal of Artificial Intelligence Research
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While in classical planning the objective is to achieve one of the equally attractive goal states at as low total action cost as possible, the objective in deterministic oversubscription planning (OSP) ...
is to achieve an as valuable as possible subset of goals within a fixed allowance of the total action cost. ...
All common heuristic search algorithms for optimal classical planning, such as A * , require admissible heuristics. ...
doi:10.1613/jair.4443
fatcat:gqxpk3jwlzbmtglj63xvndgexq
Automated Discovery of Local Search Heuristics for Satisfiability Testing
2008
Evolutionary Computation
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The development of successful metaheuristic algorithms such as local search for a difficult problems such as satisfiability testing (SAT) is a challenging task. ...
We show that several well-known SAT local search algorithms such as Walksat and Novelty are composite heuristics that are derived from novel combinations of a set of building blocks. ...
into SAT from other problem formulations such as AI planning instances. ...
doi:10.1162/evco.2008.16.1.31
pmid:18386995
fatcat:2xtt63nr7nf3lolz7lzgg4qosq
Scaling-up Generalized Planning as Heuristic Search with Landmarks
[article]
2022
arXiv
pre-print
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Landmarks are one of the most effective search heuristics for classical planning, but largely ignored in generalized planning. ...
Our two orthogonal contributions are analyzed in an ablation study, showing that both improve the state-of-the-art in GP as heuristic search, and that both benefit from each other when used in combination ...
In more detail, we build on top of the GP as heuristic search approach (Segovia-Aguas, Jiménez, and Jonsson 2021), which represents generalized plans as planning programs. Definition 2 (GP problem). ...
arXiv:2205.04850v1
fatcat:g4ynrotu2zgp3oowyozvfeskka
Friends or Foes? On Planning as Satisfiability and Abstract CNF Encodings
2009
The Journal of Artificial Intelligence Research
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Planning as satisfiability, as implemented in, for instance, the SATPLAN tool, is a highly competitive method for finding parallel step-optimal plans. ...
Surprisingly, the idea turns out to appear quite hopeless in the context of planning as satisfiability. ...
A preliminary version of this work appeared at ICAPS'06, the 16 th International Conference on Automated Planning and Scheduling (Hoffmann, Sabharwal, & Domshlak, 2006 ...
doi:10.1613/jair.2817
fatcat:wlgeq6fx6nhqhcvobi37zqr3se
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