Efficiently handling temporal knowledge in an HTN planner (original) (raw)

Temporal enhancements of an HTN planner

Current Topics in Artificial …, 2006

This paper presents some enhancements in the temporal reasoning of a Hierarchical Task Network (HTN) planner, named SIADEX, that, up to authors knowledge, no other HTN planner has. These new features include a sound partial order metric structure, deadlines, temporal landmarking or synchronization capabilities built on top of a Simple Temporal Network .

A temporal constraint network based temporal planner

Workshop of the UK Planning …, 2002

This paper describes a preliminary work on Machine T , a temporal partial order planner based on the use of temporal constraint networks to represent and propagate temporal constraints over the actions of a plan. The use of this formalism provide several advantages like the possibility of including deadline goals, makespans and imprecise temporal references able to obtain a flexible timeline for the execution of temporal plans. The expressiveness of the approach also meet the main temporal specifications of PDDL 2.1 level 3 like durative actions and invariant conditions.

Planning with Problems Requiring Temporal Coordination

2008

We present the first planner capable of reasoning with both the full semantics of PDDL2.1 (level 3) temporal planning and with numeric resources. Our planner, CRIKEY3, employs heuristic forward search, using the start-and-end semantics of PDDL2.1 to manage temporal actions. The planning phase is interleaved with a scheduling phase, using a Simple Temporal Network, in order to ensure that temporal constraints are met. To guide search, we introduce a new temporal variant of the Relaxed Planning Graph heuristic that is capable of reasoning with the features of this class of domains, along with the Timed Initial Literals of PDDL2.2. CRIKEY3 extends the state-of-the-art in handling the full temporal expressive power of PDDL2.1, including numeric temporal domains.

Using Temporal Knowledge in a Constraint-Based Planner

Incorporating domain-specic temporal knowledge into a constraint-based planner can signican tly decrease the computation time. This paper describes a method for compiling and embedding user- specied temporal information into the constraint problem translation of a planning problem. We provide empirical results for our framework implemented within the Blackbox (9) planning system; the data indicate that using temporal domain information accelerates planning. A classical planning problem is usually specied as sets of objects, actions, propositional pred- icates to describe the relationships of the objects in the world, a description of the initial state of the world, and a description of the desired nal state. The actions and predicates make up the planning domain, while a specic set of objects, an initial state, and a nal state constitute a particular planning problem. Actions act on objects; when taken, an action may change what is true about the world through its ee cts. Further, a...

Design Concepts for a new Temporal Planning Paradigm

2012

Throughout the history of space exploration, the complexity of missions has dramatically increased, from Sputnik in 1957 to MSL, a Mars rover mission launched in November 2011 with advanced autonomous capabilities. As a result, the mission plan that governs a spacecraft has also grown in complexity, pushing to the limit the capability of human operators to understand and manage it. However, the effective representation of large plans with multiple goals and constraints still represents a problem. In this paper, a novel approach to address this problem is presented. We propose a new planning paradigm named HTLN, intended to provide a compact and understandable representation of complex plans and goals based on Timeline planning and Hierarchical Temporal Networks. We also present the design of a planner based on HTLN, which enables new planning approaches that can improve the performance of present real-world domains.

Representation and Control in IxTeT, a Temporal Planner

This paper presents a temporal planner, called IxTeT. It focuses on the representation and control issues, arguing for a compromise between the expressiveness and the ei~ciency of the search. The representation relies on a point-based reified logic, associated to mldtivalued domain attributes. Hieraxchical planning operators ot~er an expressive description, with parallelism, durations, effects and conditions at various moments of the action. Time in the input scenario enables to take into account predicted forthcoming events and to plan in a dynamic world. A compilation procedure checks the consistency of the operators specified by the user. The control relies on the use of causal-links, A, algorithm, and an extended least-commitment strategy. It uses two important procedures, called C~feasibility" and "satisfiability =, dealing respectively with goal decomposition and conflict resolution: GHALLAB 61

On Guiding Search in HTN Temporal Planning with non Temporal Heuristics

arXiv (Cornell University), 2023

The Hierarchical Task Network (HTN) formalism is used to express a wide variety of planning problems as task decompositions, and many techniques have been proposed to solve them. However, few works have been done on temporal HTN. This is partly due to the lack of a formal and consensual definition of what a temporal hierarchical planning problem is as well as the difficulty to develop heuristics in this context. In response to these inconveniences, we propose in this paper a new general POCL (Partial Order Causal Link) approach to represent and solve a temporal HTN problem by using existing heuristics developed to solve non temporal problems. We show experimentally that this approach is performant and can outperform the existing ones.

Exploiting Domain Knowledge with a Concurrent Hierarchical Planner

2000

Based on recent research about coordinating concurrent hierarchical plans (CHiPs), we introduce a sound and complete hierarchical planner that can better reason about precomputed conditions (summary information) of abstract plans to potentially make better re nement decisions than previous approaches. A reasonable criticism of this technique is that the summary information can grow exponentially as it is propagated up a plan hierarchy. This paper analyzes the complexity of the problem to show that in spite of this exponential growth, nding solutions at higher levels is still exponentially cheaper than at lower levels. In addition, this paper o ers heuristics, including \fewest threats rst" (FTF) and \expand most threats rst" (EMTF), that take advantage of summary information to smartly direct the search for a global plan. Experiments show that for a particular domain these heuristics could greatly improve the search for the optimal global plan compared to two other heuristics (FAF and ExCon) that have both been successful in Hierarchical Task Network (HTN) planning.

Managing concurrency in temporal planning using planner-scheduler interaction

Artificial Intelligence, 2009

Metric temporal planning involves both selecting and organising actions to satisfy the goals and also assigning to each of these actions its start time and, where necessary, its duration. The assignment of start times to actions is a central concern of scheduling. In pddl2.1, the widely adopted planning domain description language standard, metric temporal planning problems are described using actions with durations. A large number of planners have been developed to handle this language, but the great majority of them are fundamentally limited in the class of temporal problems they can solve. In this paper, we review the source of this limitation and present an approach to metric temporal planning that is not so restricted. Our approach links planning and scheduling algorithms into a planner, Crikey, that can successfully tackle a wide range of temporal problems. We show how Crikey can be simplified to solve a wide and interesting subset of metric temporal problems, while remaining competitive with other temporal planners that are unable to handle required concurrency. We provide empirical data comparing the performance of this planner, Crikey SHE , our original version, Crikey, and a range of other modern temporal planners. Our contribution is to describe the first competitive planner capable of solving problems that require concurrent actions.