A CSP-Based Approach for Temporal Constraints in Temporal Planning

2012 ◽  
Vol 35 (8) ◽  
pp. 1759
Author(s):  
Li-Hua WU ◽  
Ai-Xiang CHEN ◽  
Yun-Fei JIANG ◽  
Rui BIAN
Keyword(s):  
Temporal Constraints ◽  
Temporal Planning

scholarly journals An Approach to Temporal Planning and Scheduling in Domains with Predictable Exogenous Events

2006 ◽  
Vol 25 ◽  
pp. 187-231 ◽  
Author(s):  
A. Gerevini ◽  
A. Saetti ◽  
I. Serina
Keyword(s):  
Statistical Analysis ◽  
Time Windows ◽  
Temporal Reasoning ◽  
Temporal Constraints ◽  
Planning And Scheduling ◽  
Temporal Planning ◽  
Cpu Time ◽  
Planning Framework ◽  
Extra Difficulty ◽  
International Planning

The treatment of exogenous events in planning is practically important in many real-world domains where the preconditions of certain plan actions are affected by such events. In this paper we focus on 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. When actions have durations, handling such temporal constraints adds an extra difficulty to planning. We propose an approach to planning in these domains which integrates constraint-based temporal reasoning into a graph-based planning framework using local search. Our techniques are implemented in a planner that took part in the 4th International Planning Competition (IPC-4). A statistical analysis of the results of IPC-4 demonstrates the effectiveness of our approach in terms of both CPU-time and plan quality. Additional experiments show the good performance of the temporal reasoning techniques integrated into our planner.

scholarly journals Efficient Temporal Planning Using Metastates

2019 ◽  
Vol 33 ◽  
pp. 7554-7561 ◽  
Author(s):  
Amanda Coles ◽  
Andrew Coles ◽  
J. Christopher Beck
Keyword(s):  
State Space ◽  
State Of The Art ◽  
The State ◽  
The Other ◽  
Temporal Constraints ◽  
State Space Explosion ◽  
Temporal Planning ◽  
State Space Search ◽  
Temporal Inconsistency

When performing temporal planning as forward state-space search, effective state memoisation is challenging. Whereas in classical planning, two states are equal if they have the same facts and variable values, in temporal planning this is not the case: as the plans that led to the two states are subject to temporal constraints, one might be extendable into at temporally valid plan, while the other might not. In this paper, we present an approach for reducing the state space explosion that arises due to having to keep many copies of the same ‘classically’ equal state – states that are classically equal are aggregated into metastates, and these are separated lazily only in the case of temporal inconsistency. Our evaluation shows that this approach, implemented in OPTIC and compared to existing state-of-the-art memoisation techniques, improves performance across a range of temporal domains.

A Planning Algorithm with Temporal Constraints in the Working Procedures

2013 ◽  
Vol 760-762 ◽  
pp. 1786-1789
Author(s):  
Xiao Long Chai
Keyword(s):  
Ant Colony Algorithm ◽  
Convergence Acceleration ◽  
Research Area ◽  
Ant Colony ◽  
Temporal Constraints ◽  
Temporal Planning ◽  
Control Rules ◽  
Real World Applications ◽  
Planning Algorithm ◽  
Planning Problems

Temporal planning is a broad research area in automated planning. In most real-world applications such as the problems of working procedures planning, many real planning problems often require the planning goals can be satisfied in shorter time and some temporal constraints should be satisfied in the planning answer. In this paper, the ant colony algorithm under the temporal constraints is presented which with the heuristic control rules and the evaluation tactics in the framework of the ant colony planning algorithm. The searching way of the algorithm has the character of global and parallel. And it has the ability of convergence acceleration in the solution searching.

scholarly journals Temporal Planning with Temporal Metric Trajectory Constraints

2019 ◽  
Vol 33 ◽  
pp. 7675-7682 ◽  
Author(s):  
Andrea Micheli ◽  
Enrico Scala
Keyword(s):  
Industrial Applications ◽  
Timing Constraints ◽  
Temporal Constraints ◽  
Forward Search ◽  
New Formalism ◽  
Temporal Planning ◽  
Precise Timing ◽  
Alternative State ◽  
Planning Approaches

In several industrial applications of planning, complex temporal metric trajectory constraints are needed to adequately model the problem at hand. For example, in production plants, items must be processed following a “recipe” of steps subject to precise timing constraints. Modeling such domains is very challenging in existing action-based languages due to the lack of sufficiently expressive trajectory constraints.We propose a novel temporal planning formalism allowing quantified temporal constraints over execution timing of action instances. We build on top of instantaneous actions borrowed from classical planning and add expressive temporal constructs. The paper details the semantics of our new formalism and presents a solving technique grounded in classical, heuristic forward search planning. Our experiments prove the proposed framework superior to alternative state-of-theart planning approaches on industrial benchmarks, and competitive with similar solving methods on well known benchmarks took from the planning competition.

scholarly journals Complexity Bounds for the Controllability of Temporal Networks with Conditions, Disjunctions, and Uncertainty (Extended Abstract)

2019 ◽  
Author(s):  
Nikhil Bhargava ◽  
Brian C. Williams
Keyword(s):  
Computational Complexity ◽  
Real World ◽  
Temporal Constraints ◽  
Temporal Network ◽  
Temporal Networks ◽  
Temporal Uncertainty ◽  
Complexity Bounds ◽  
Temporal Planning ◽  
Underlying Network

In temporal planning, many different temporal network formalisms are used to model real world situations. Each of these formalisms has different features which affect how easy it is to determine whether the underlying network of temporal constraints is consistent. While many of the simpler models have been well-studied from a computational complexity perspective, the algorithms developed for advanced models which combine features have very loose complexity bounds. In this work, we provide tight completeness bounds for strong, weak, and dynamic controllability checking of temporal networks that have conditions, disjunctions, and temporal uncertainty. Our work exposes some of the subtle differences between these different structures and, remarkably, establishes a guarantee that all of these problems are computable in PSPACE.

scholarly journals Temporal Planning with Intermediate Conditions and Effects

2020 ◽  
Vol 34 (06) ◽  
pp. 9975-9982
Author(s):  
Alessandro Valentini ◽  
Andrea Micheli ◽  
Alessandro Cimatti
Keyword(s):  
Heuristic Search ◽  
Temporal Constraints ◽  
Planning Systems ◽  
Search Technique ◽  
Arbitrary Time ◽  
Temporal Planning ◽  
Definition Of ◽  
Better Than

Automated temporal planning is the technology of choice when controlling systems that can execute more actions in parallel and when temporal constraints, such as deadlines, are needed in the model. One limitation of several action-based planning systems is that actions are modeled as intervals having conditions and effects only at the extremes and as invariants, but no conditions nor effects can be specified at arbitrary points or sub-intervals.In this paper, we address this limitation by providing an effective heuristic-search technique for temporal planning, allowing the definition of actions with conditions and effects at any arbitrary time within the action duration. We experimentally demonstrate that our approach is far better than standard encodings in PDDL 2.1 and is competitive with other approaches that can (directly or indirectly) represent intermediate action conditions or effects.

scholarly journals ITSAT: An Efficient SAT-Based Temporal Planner

2015 ◽  
Vol 53 ◽  
pp. 541-632 ◽  
Author(s):  
Masood Feyzbakhsh Rankooh ◽  
Gholamreza Ghassem-Sani
Keyword(s):  
State Space ◽  
State Of The Art ◽  
Relation Extraction ◽  
The State ◽  
Parallel Execution ◽  
Temporal Constraints ◽  
Continuous Variables ◽  
Temporal Planning ◽  
Execution Semantics ◽  
Planning Problems

Planning as satisfiability is known as an efficient approach to deal with many types of planning problems. However, this approach has not been competitive with the state-space based methods in temporal planning. This paper describes ITSAT as an efficient SAT-based (satisfiability based) temporal planner capable of temporally expressive planning. The novelty of ITSAT lies in the way it handles temporal constraints of given problems without getting involved in the difficulties of introducing continuous variables into the corresponding satisfiability problems. We also show how, as in SAT-based classical planning, carefully devised preprocessing and encoding schemata can considerably improve the efficiency of SAT-based temporal planning. We present two preprocessing methods for mutex relation extraction and action compression. We also show that the separation of causal and temporal reasoning enables us to employ compact encodings that are based on the concept of parallel execution semantics. Although such encodings have been shown to be quite effective in classical planning, ITSAT is the first temporal planner utilizing this type of encoding. Our empirical results show that not only does ITSAT outperform the state-of-the-art temporally expressive planners, it is also competitive with the fast temporal planners that cannot handle required concurrency.

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