scholarly journals Exploring Lifted Planning Encodings in Essence Prime

2021 ◽  
Author(s):  
Joan Espasa ◽  
Jordi Coll ◽  
Ian Miguel ◽  
Mateu Villaret
Keyword(s):  
State Space ◽  
Programming Language ◽  
Constraint Programming ◽  
Community Planning ◽  
Automated Planning ◽  
Search Method ◽  
Compact Representation ◽  
Space Planning ◽  
International Planning ◽  
Planning Problems

State-space planning is the de-facto search method of the automated planning community. Planning problems are typically expressed in the Planning Domain Definition Language (PDDL), where action and variable templates describe the sets of actions and variables that occur in the problem. Typically, a planner begins by generating the full set of instantiations of these templates, which in turn are used to derive useful heuristics that guide the search. Thanks to this success, there has been limited research in other directions. We explore a different approach, keeping the compact representation by directly reformulating the problem in PDDL into ESSENCE PRIME, a Constraint Programming language with support for distinct solving technologies including SAT and SMT. In particular, we explore two different encodings from PDDL to ESSENCE PRIME, how they represent action parameters, and their performance. The encodings are able to maintain the compactness of the PDDL representation, and while they differ slightly, they perform quite differently on various instances from the International Planning Competition.

scholarly journals Compilation-Based Approaches to Parallel Planning: An Empirical Comparison

2021 ◽  
Vol 34 (1) ◽  
Author(s):  
Kristýna Pantůčková ◽  
Roman Barták
Keyword(s):  
Programming Language ◽  
Constraint Satisfaction ◽  
Constraint Satisfaction Problem ◽  
Automated Planning ◽  
Boolean Satisfiability ◽  
Planning Problem ◽  
Empirical Comparison ◽  
Boolean Satisfiability Problem ◽  
International Planning ◽  
Planning Problems

Automated planning deals with finding a sequence of actions, a plan, to reach a goal. One of the possible approaches to automated planning is a compilation of a planning problem to a Boolean satisfiability problem or to a constraint satisfaction problem, which takes direct advantage of the advancements of satisfiability and constraint satisfaction solvers. This paper provides a comparison of three encodings proposed for the compilation of planning problems: Transition constraints for parallel planning (TCPP), Relaxed relaxed exist-Step encoding and Reinforced Encoding. We implemented the encodings using the programming language Picat 2.8, we suggested certain modifications, and we compared the performance of the encodings on benchmarks from international planning competitions.

scholarly journals REINFORCED ENCODING FOR PLANNING AS SAT

2015 ◽  
Vol 2 (2) ◽  
pp. 1-7
Author(s):  
Tomáš Balyo ◽  
Roman Barták ◽  
Otakar Trunda
Keyword(s):  
Automated Planning ◽  
The Other ◽  
Benchmark Problems ◽  
Planning Problem ◽  
Encoding Scheme ◽  
International Planning ◽  
Planning Problems

Solving planning problems via translation to satisfiability (SAT) is one of the most successful approaches to automated planning. We propose a new encoding scheme, called Reinforced Encoding, which encodes a planning problem represented in the SAS+ formalism into SAT. The Reinforced Encoding is a combination of the transition-based SASE encoding with the classical propositional encoding. In our experiments we compare our new encoding to other known SAS+ based encodings. The results indicate, that he Reinforced encoding performs well on the benchmark problems of the 2011 International Planning Competition and can outperform all the other known encodings for several domains.

scholarly journals HMCTS-OP: Hierarchical MCTS Based Online Planning in the Asymmetric Adversarial Environment

Symmetry ◽  
2020 ◽  
Vol 12 (5) ◽  
pp. 719
Author(s):  
Lina Lu ◽  
Wanpeng Zhang ◽  
Xueqiang Gu ◽  
Xiang Ji ◽  
Jing Chen
Keyword(s):  
Computational Complexity ◽  
State Space ◽  
Planning Horizon ◽  
Search Space ◽  
Monte Carlo Tree Search ◽  
Practical Applications ◽  
Online Planning ◽  
Planning Framework ◽  
Planning Methods ◽  
Planning Problems

The Monte Carlo Tree Search (MCTS) has demonstrated excellent performance in solving many planning problems. However, the state space and the branching factors are huge, and the planning horizon is long in many practical applications, especially in the adversarial environment. It is computationally expensive to cover a sufficient number of rewarded states that are far away from the root in the flat non-hierarchical MCTS. Therefore, the flat non-hierarchical MCTS is inefficient for dealing with planning problems with a long planning horizon, huge state space, and branching factors. In this work, we propose a novel hierarchical MCTS-based online planning method named the HMCTS-OP to tackle this issue. The HMCTS-OP integrates the MAXQ-based task hierarchies and the hierarchical MCTS algorithms into the online planning framework. Specifically, the MAXQ-based task hierarchies reduce the search space and guide the search process. Therefore, the computational complexity is significantly reduced. Moreover, the reduction in the computational complexity enables the MCTS to perform a deeper search to find better action in a limited time. We evaluate the performance of the HMCTS-OP in the domain of online planning in the asymmetric adversarial environment. The experiment results show that the HMCTS-OP outperforms other online planning methods in this domain.

scholarly journals Bringing Order to Chaos – A Compact Representation of Partial Order in SAT-Based HTN Planning

2019 ◽  
Vol 33 ◽  
pp. 7520-7529 ◽  
Author(s):  
Gregor Behnke ◽  
Daniel Höller ◽  
Susanne Biundo
Keyword(s):  
Partial Order ◽  
Propositional Logic ◽  
State Of The Art ◽  
Partial Ordering ◽  
Compact Representation ◽  
Planning Techniques ◽  
Model Complex ◽  
Htn Planning ◽  
Sat Solver ◽  
Planning Problems

HTN planning provides an expressive formalism to model complex application domains. It has been widely used in realworld applications. However, the development of domainindependent planning techniques for such models is still lacking behind. The need to be informed about both statetransitions and the task hierarchy makes the realisation of search-based approaches difficult, especially with unrestricted partial ordering of tasks in HTN domains. Recently, a translation of HTN planning problems into propositional logic has shown promising empirical results. Such planners benefit from a unified representation of state and hierarchy, but until now require very large formulae to represent partial order. In this paper, we introduce a novel encoding of HTN Planning as SAT. In contrast to related work, most of the reasoning on ordering relations is not left to the SAT solver, but done beforehand. This results in much smaller formulae and, as shown in our evaluation, in a planner that outperforms previous SAT-based approaches as well as the state-of-the-art in search-based HTN 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

scholarly journals Monotonic Set-Extended Prefix Rewriting and Verification of Recursive Ping-Pong Protocols

2006 ◽  
Vol 13 (14) ◽  
Author(s):  
Giorgio Delzanno ◽  
Javier Esparza ◽  
Jirí Srba
Keyword(s):  
Programming Language ◽  
Constraint Programming ◽  
Ping Pong ◽  
Analysis And Synthesis ◽  
Security Properties ◽  
Full Analysis ◽  
Recursive Definitions ◽  
Control State ◽  
Concurrent Constraint Programming

Ping-pong protocols with recursive definitions of agents, but without any active intruder, are a Turing powerful model. We show that under the environment sensitive semantics (i.e. by adding an active intruder capable of storing all exchanged messages including full analysis and synthesis of messages) some verification problems become decidable. In particular we give an algorithm to decide control state reachability, a problem related to security properties like secrecy and authenticity. The proof is via a reduction to a new prefix rewriting model called Monotonic Set-extended Prefix rewriting (MSP). We demonstrate further applicability of the introduced model by encoding a fragment of the ccp (concurrent constraint programming) language into MSP.

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.

scholarly journals Imperfect Match: PDDL 2.1 and Real Applications

2003 ◽  
Vol 20 ◽  
pp. 133-137 ◽  
Author(s):  
M. S. Boddy
Keyword(s):  
Lingua Franca ◽  
Planning Models ◽  
Solution Methods ◽  
International Planning ◽  
Planning Problems

PDDL was originally conceived and constructed as a lingua franca for the International Planning Competition. PDDL2.1 embodies a set of extensions intended to support the expression of something closer to ``real planning problems.'' This objective has only been partially achieved, due in large part to a deliberate focus on not moving too far from classical planning models and solution methods.

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