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In recent years research in the planning community has moved increasingly toward s application of planners to realistic problems involving both time and many typ es of resources. For example, interest in planning demonstrated by the space…

Artificial Intelligence · Computer Science 2011-06-24 M. Fox , D. Long

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…

Artificial Intelligence · Computer Science 2011-10-13 A. Gerevini , A. Saetti , I. Serina

In real-world applications, the ability to reason about incomplete knowledge, sensing, temporal notions, and numeric constraints is vital. While several AI planners are capable of dealing with some of these requirements, they are mostly…

Artificial Intelligence · Computer Science 2022-07-21 Yaniel Carreno , Yvan Petillot , Ronald P. A. Petrick

This paper describes Picat's planner, its implementation, and planning models for several domains used in International Planning Competition (IPC) 2014. Picat's planner is implemented by use of tabling. During search, every state…

Artificial Intelligence · Computer Science 2020-02-19 Neng-Fa Zhou , Roman Bartak , Agostino Dovier

Timeline-based planning is an approach originally developed in the context of space mission planning and scheduling, where problem domains are modelled as systems made of a number of independent but interacting components, whose behaviour…

Artificial Intelligence · Computer Science 2021-07-26 Nicola Gigante

Over the last year, the amount of research in hierarchical planning has increased, leading to significant improvements in the performance of planners. However, the research is diverging and planners are somewhat hard to compare against each…

Artificial Intelligence · Computer Science 2019-09-11 D. Höller , G. Behnke , P. Bercher , S. Biundo , H. Fiorino , D. Pellier , R. Alford

Temporal planning is an extension of classical planning involving concurrent execution of actions and alignment with temporal constraints. Durative actions along with invariants allow for modeling domains in which multiple agents operate in…

Artificial Intelligence · Computer Science 2023-07-25 Marco De Bortoli , Lukáš Chrpa , Martin Gebser , Gerald Steinbauer-Wagner

We present some techniques for planning in domains specified with the recent standard language PDDL2.1, supporting 'durative actions' and numerical quantities. These techniques are implemented in LPG, a domain-independent planner that took…

Artificial Intelligence · Computer Science 2011-06-28 A. Gerevini , A. Saetti , I. Serina

Replanning in temporal logic tasks is extremely difficult during the online execution of robots. This study introduces an effective path planner that computes solutions for temporal logic goals and instantly adapts to non-static and…

Robotics · Computer Science 2023-02-23 Yizhou Chen , Ruoyu Wang , Xinyi Wang , Ben M. Chen

Automated Planning is one of the main research field of Artificial Intelligence since its beginnings. Research in Automated Planning aims at developing general reasoners (i.e., planners) capable of automatically solve complex problems.…

Artificial Intelligence · Computer Science 2019-05-15 Alessandro Umbrico

Despite recent progress in AI planning, many benchmarks remain challenging for current planners. In many domains, the performance of a planner can greatly be improved by discovering and exploiting information about the domain structure that…

Artificial Intelligence · Computer Science 2011-09-13 A. Botea , M. Enzenberger , M. Mueller , J. Schaeffer

Task and motion planning (TAMP) frameworks address long and complex planning problems by integrating high-level task planners with low-level motion planners. However, existing TAMP methods rely heavily on the manual design of planning…

Robotics · Computer Science 2025-09-09 Jinbang Huang , Allen Tao , Rozilyn Marco , Miroslav Bogdanovic , Jonathan Kelly , Florian Shkurti

Temporal planning often involves numeric effects that are directly proportional to their action's duration. These include continuous effects, where a numeric variable is subjected to a rate of change while the action is being executed, and…

Artificial Intelligence · Computer Science 2022-02-01 Josef Bajada , Maria Fox , Derek Long

Planning has been part of the core pursuit for artificial intelligence since its conception, but earlier AI agents mostly focused on constrained settings because many of the cognitive substrates necessary for human-level planning have been…

Computation and Language · Computer Science 2024-10-24 Jian Xie , Kai Zhang , Jiangjie Chen , Tinghui Zhu , Renze Lou , Yuandong Tian , Yanghua Xiao , Yu Su

This paper reports the outcome of the third in the series of biennial international planning competitions, held in association with the International Conference on AI Planning and Scheduling (AIPS) in 2002. In addition to describing the…

Artificial Intelligence · Computer Science 2011-06-30 M. Fox , D. Long

In this paper we consider three different kinds of domain-dependent control knowledge (temporal, procedural and HTN-based) that are useful in planning. Our approach is declarative and relies on the language of logic programming with answer…

Artificial Intelligence · Computer Science 2007-05-23 Tran Cao Son , Chitta Baral , Nam Tran , Sheila McIlraith

We provide an overview of the organization and results of the deterministic part of the 4th International Planning Competition, i.e., of the part concerned with evaluating systems doing deterministic planning. IPC-4 attracted even more…

Artificial Intelligence · Computer Science 2011-09-27 S. Edelkamp , J. Hoffmann

Ontologies are known for their ability to organize rich metadata, support the identification of novel insights via semantic queries, and promote reuse. In this paper, we consider the problem of automated planning, where the objective is to…

Artificial Intelligence · Computer Science 2024-07-09 Bharath Muppasani , Vishal Pallagani , Biplav Srivastava , Raghava Mutharaju , Michael N. Huhns , Vignesh Narayanan

We propose some domain-independent techniques for bringing well-founded partial-order planners closer to practicality. The first two techniques are aimed at improving search control while keeping overhead costs low. One is based on a simple…

Artificial Intelligence · Computer Science 2009-09-25 A. Gerevini , L. Schubert

The assumption of complete domain knowledge is not warranted for robot planning and decision-making in the real world. It could be due to design flaws or arise from domain ramifications or qualifications. In such cases, existing planning…

Artificial Intelligence · Computer Science 2020-11-19 Akshay Sharma , Piyush Rajesh Medikeri , Yu Zhang
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