scholarly journals Temporal Planning with Temporal Metric Trajectory Constraints

Author(s):  
Andrea Micheli ◽  
Enrico Scala

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.

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

1992 ◽  
Vol 03 (03) ◽  
pp. 303-322
Author(s):  
PADMANABHAN KRISHNAN

In this paper we define an operational semantics for a timed version of a Calculus of Communicating Systems (CCS) [1], We also consider timing constraints that a process needs to satisfy and develop preorder relations induced by the temporal constraints.


2006 ◽  
Vol 25 ◽  
pp. 187-231 ◽  
Author(s):  
A. Gerevini ◽  
A. Saetti ◽  
I. Serina

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.


Author(s):  
Amanda Coles ◽  
Andrew Coles ◽  
J. Christopher Beck

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.


2013 ◽  
Vol 760-762 ◽  
pp. 1786-1789
Author(s):  
Xiao Long Chai

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.


Author(s):  
Nikhil Bhargava ◽  
Brian C. Williams

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.


2017 ◽  
Vol 8 (3) ◽  
pp. 38-57 ◽  
Author(s):  
Radja Radja Boukharrou ◽  
Jean-Michel Ilié ◽  
Djamel Eddine Saidouni

This paper presents an algebraic language, called Time-AgLOTOS, to describe time-dependent behavior of intelligent agent for the design of Ambient Intelligence systems. This specification model provides a theoretical foundation for performing planning under timing constraints. Based on a true-concurrency semantics, a contextual model, called Spatio-Temporal Planning System (STPS), is developed to capture all possible evolutions of an agent plan including context changes. The STPS provides formal description of possible actions to perform supporting timing constraints, action duration and spatial information. This structure offers new possibilities and strategies for taking agent real-time decisions in context-awareness manner.


2020 ◽  
Vol 34 (06) ◽  
pp. 9975-9982
Author(s):  
Alessandro Valentini ◽  
Andrea Micheli ◽  
Alessandro Cimatti

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.


Sign in / Sign up

Export Citation Format

Share Document