scholarly journals Planning with preferences using logic programming

2006 ◽  
Vol 6 (5) ◽  
pp. 559-607 ◽  
Author(s):  
TRAN CAO SON ◽  
ENRICO PONTELLI
Keyword(s):  
Logic Programming ◽  
Answer Set Programming ◽  
Planning Problem ◽  
Declarative Language ◽  
High Level ◽  
Planning Problems ◽  
Answer Set

We present a declarative language, ${\cal PP}$, for the high-level specification of preferences between possible solutions (or trajectories) of a planning problem. This novel language allows users to elegantly express non-trivial, multi-dimensional preferences and priorities over such preferences. The semantics of ${\cal PP}$ allows the identification of most preferred trajectories for a given goal. We also provide an answer set programming implementation of planning problems with ${\cal PP}$ preferences.

scholarly journals Meta-Interpretive Learning Using HEX-Programs

2019 ◽  
Author(s):  
Tobias Kaminski ◽  
Thomas Eiter ◽  
Katsumi Inoue
Keyword(s):  
Logic Programming ◽  
Inductive Logic Programming ◽  
Inductive Logic ◽  
Answer Set Programming ◽  
Search Space ◽  
Recent Approach ◽  
Performance Gains ◽  
Pruning Techniques ◽  
Answer Set

Meta-Interpretive Learning (MIL) is a recent approach for Inductive Logic Programming (ILP) implemented in Prolog. Alternatively, MIL-problems can be solved by using Answer Set Programming (ASP), which may result in performance gains due to efficient conflict propagation. However, a straightforward MIL-encoding results in a huge size of the ground program and search space. To address these challenges, we encode MIL in the HEX-extension of ASP, which mitigates grounding issues, and we develop novel pruning techniques.

Action language ℬ𝒞+

2015 ◽  
Vol 30 (4) ◽  
pp. 899-922 ◽  
Author(s):  
Joseph Babb ◽  
Joohyung Lee
Keyword(s):  
Main Idea ◽  
Answer Set Programming ◽  
Stable Model ◽  
Formal Models ◽  
Transition Systems ◽  
Action Languages ◽  
Action Language ◽  
Language Constructs ◽  
High Level ◽  
Answer Set

Abstract Action languages are formal models of parts of natural language that are designed to describe effects of actions. Many of these languages can be viewed as high-level notations of answer set programs structured to represent transition systems. However, the form of answer set programs considered in the earlier work is quite limited in comparison with the modern Answer Set Programming (ASP) language, which allows several useful constructs for knowledge representation, such as choice rules, aggregates and abstract constraint atoms. We propose a new action language called BC +, which closes the gap between action languages and the modern ASP language. The main idea is to define the semantics of BC + in terms of general stable model semantics for propositional formulas, under which many modern ASP language constructs can be identified with shorthands for propositional formulas. Language BC  + turns out to be sufficiently expressive to encompass the best features of other action languages, such as languages B , C , C + and BC . Computational methods available in ASP solvers are readily applicable to compute BC +, which led to an implementation of the language by extending system cplus2asp .

Declarative Planning and Knowledge Representation in an Action Language

2011 ◽  
pp. 192-221 ◽  
Author(s):  
Thomas Eiter ◽  
Wolfgang Faber ◽  
Gerald Pfeifer
Keyword(s):  
Knowledge Representation ◽  
Logic Programming ◽  
Planning System ◽  
Epistemic State ◽  
Action Languages ◽  
Knowledge States ◽  
Action Language ◽  
High Level ◽  
Planning Problems ◽  
Complex Planning

This chapter introduces planning and knowledge representation in the declarative action language K. Rooted in the area of Knowledge Representation & Reasoning, action languages like K allow the formalization of complex planning problems involving non-determinism and incomplete knowledge in a very flexible manner. By giving an overview of existing planning languages and comparing these against our language, we aim on further promoting the applicability and usefulness of high-level action languages in the area of planning. As opposed to previously existing languages for modeling actions and change, K adopts a logic programming view where fluents representing the epistemic state of an agent might be true, false or undefined in each state. We will show that this view of knowledge states can be fruitfully applied to several well-known planning domains from the literature as well as novel planning domains. Remarkably, K often allows to model problems more concisely than previous action languages. All the examples given can be tested in an available implementation, the DLVK planning system.

A Roadmap on Updates

2009 ◽  
pp. 2261-2267
Author(s):  
Fernando Zacarías Flores ◽  
Dionicio Zacarías Flores ◽  
Rosalba Cuapa Canto ◽  
Luis Miguel Guzmán Muñoz
Keyword(s):  
Standard Model ◽  
Logic Programming ◽  
Structural Properties ◽  
Relational Databases ◽  
Logic Program ◽  
Answer Set Programming ◽  
Central Issue ◽  
The Standard Model ◽  
Answer Set

Updates, is a central issue in relational databases and knowledge databases. In the last years, it has been well studied in the non-monotonic reasoning paradigm. Several semantics for logic program updates have been proposed (Brewka, Dix, & Knonolige 1997), (De Schreye, Hermenegildo, & Pereira, 1999) (Katsumo & Mendelzon, 1991). However, recently a set of proposals has been characterized to propose mechanisms of updates based on logic and logic programming. All these mechanisms are built on semantics based on structural properties (Eiter, Fink, Sabattini & Thompits, 2000) (Leite, 2002) (Banti, Alferes & Brogi, 2003) (Zacarias, 2005). Furthermore, all these semantic ones coincide in considering the AGM proposal as the standard model in the update theory, for their wealth in properties. The AGM approach, introduced in (Alchourron, Gardenfors & Makinson, 1985) is the dominating paradigm in the area, but in the context of monotonic logic. All these proposals analyze and reinterpret the AGM postulates under the Answer Set Programming (ASP) such as (Eiter, Fink, Sabattini & Thompits, 2000). However, the majority of the adapted AGM and update postulates are violated by update programs, as shown in(De Schreye, Hermenegildo, & Pereira, 1999).

scholarly journals onlineSPARC: A Programming Environment for Answer Set Programming

2018 ◽  
Vol 19 (2) ◽  
pp. 262-289 ◽  
Author(s):  
ELIAS MARCOPOULOS ◽  
YUANLIN ZHANG
Keyword(s):  
High School Students ◽  
Logic Programming ◽  
Answer Set Programming ◽  
Programming Environment ◽  
Logic Programs ◽  
School Students ◽  
Major Barrier ◽  
Simple Interface ◽  
Answer Sets ◽  
Answer Set

AbstractRecent progress in logic programming (e.g. the development of the answer set programming (ASP) paradigm) has made it possible to teach it to general undergraduate and even middle/high school students. Given the limited exposure of these students to computer science, the complexity of downloading, installing, and using tools for writing logic programs could be a major barrier for logic programming to reach a much wider audience. We developed onlineSPARC, an online ASP environment with a self-contained file system and a simple interface. It allows users to type/edit logic programs and perform several tasks over programs, including asking a query to a program, getting the answer sets of a program, and producing a drawing/animation based on the answer sets of a program.

scholarly journals Reasoning and planning with sensing actions, incomplete information, and static causal laws using answer set programming

2007 ◽  
Vol 7 (4) ◽  
pp. 377-450 ◽  
Author(s):  
PHAN HUY TU ◽  
TRAN CAO SON ◽  
CHITTA BARAL
Keyword(s):  
Incomplete Information ◽  
Answer Set Programming ◽  
Planning Problem ◽  
Possible World ◽  
Initial State ◽  
Possible World Semantics ◽  
Sensing Actions ◽  
Action Theories ◽  
Causal Laws ◽  
Answer Set

AbstractWe extend the 0-approximation of sensing actions and incomplete information in Son and Baral (2001) to action theories with static causal laws and prove its soundness with respect to the possible world semantics. We also show that the conditional planning problem with respect to this approximation isNP-complete. We then present an answer set programming based conditional planner, called ASCP, that is capable of generating both conformant plans and conditional plans in the presence of sensing actions, incomplete information about the initial state, and static causal laws. We prove the correctness of our implementation and argue that our planner is sound and complete with respect to the proposed approximation. Finally, we present experimental results comparing ASCP to other planners.

scholarly journals Determining Action Reversibility in STRIPS Using Answer Set and Epistemic Logic Programming

2021 ◽  
pp. 1-17
Author(s):  
WOLFGANG FABER ◽  
MICHAEL MORAK ◽  
LUKÁŠ CHRPA
Keyword(s):  
Logic Programming ◽  
Epistemic Logic ◽  
Answer Set Programming ◽  
Reasoning About Actions ◽  
Original State ◽  
Computational Problem ◽  
Compare And Contrast ◽  
Answer Set

Abstract In the context of planning and reasoning about actions and change, we call an action reversible when its effects can be reverted by applying other actions, returning to the original state. Renewed interest in this area has led to several results in the context of the PDDL language, widely used for describing planning tasks. In this paper, we propose several solutions to the computational problem of deciding the reversibility of an action. In particular, we leverage an existing translation from PDDL to Answer Set Programming (ASP), and then use several different encodings to tackle the problem of action reversibility for the STRIPS fragment of PDDL. For these, we use ASP, as well as Epistemic Logic Programming (ELP), an extension of ASP with epistemic operators, and compare and contrast their strengths and weaknesses.

High-level synthesis of on-chip multiprocessor architectures based on answer set programming

2018 ◽  
Vol 117 ◽  
pp. 161-179 ◽  
Author(s):  
Christophe Bobda ◽  
Franck Yonga ◽  
Martin Gebser ◽  
Harold Ishebabi ◽  
Torsten Schaub
Keyword(s):  
Answer Set Programming ◽  
Chip Multiprocessor ◽  
High Level Synthesis ◽  
Multiprocessor Architectures ◽  
On Chip ◽  
High Level ◽  
Answer Set

scholarly journals A Case for Query-driven Predicate Answer Set Programming

10.29007/ngm2 ◽  
2018 ◽  
Author(s):  
Gopal Gupta ◽  
Elmer Salazar ◽  
Kyle Marple ◽  
Zhuo Chen ◽  
Farhad Shakerin
Keyword(s):  
Logic Programming ◽  
Common Sense ◽  
Automated Reasoning ◽  
Answer Set Programming ◽  
Stable Model ◽  
Common Sense Reasoning ◽  
Knowledge Based ◽  
Full Power ◽  
Programming Systems ◽  
Answer Set

Answer Set Programming (ASP) has emerged as a successful paradigm for developing intelligent applications. ASP is based on adding negation as failure to logic programming under the stable model semantics regime. ASP allows for sophisticated reasoning mechanisms that are employed by humans to be modeled elegantly. We argue that being able to model common sense reasoning as used by humans is critical for success of automated reasoning. We also argue that extending answer programming systems to general predicates is critical to realizing the full power of ASP. Goal-directed predicate ASP systems are needed to make the ASP technology practical for building large, scalable knowledge-based applications.

scholarly journals Answer Set Planning Under Action Costs

2003 ◽  
Vol 19 ◽  
pp. 25-71 ◽  
Author(s):  
T. Eiter ◽  
W. Faber ◽  
N. Leone ◽  
G. Pfeifer ◽  
A. Polleres
Keyword(s):  
Answer Set Programming ◽  
Optimality Criteria ◽  
Experimental Results ◽  
Logic Programs ◽  
Planning Systems ◽  
Planning Problems ◽  
Answer Set

Recently, planning based on answer set programming has been proposed as an approach towards realizing declarative planning systems. In this paper, we present the language Kc, which extends the declarative planning language K by action costs. Kc provides the notion of admissible and optimal plans, which are plans whose overall action costs are within a given limit resp. minimum over all plans (i.e., cheapest plans). As we demonstrate, this novel language allows for expressing some nontrivial planning tasks in a declarative way. Furthermore, it can be utilized for representing planning problems under other optimality criteria, such as computing ``shortest'' plans (with the least number of steps), and refinement combinations of cheapest and fastest plans. We study complexity aspects of the language Kc and provide a transformation to logic programs, such that planning problems are solved via answer set programming. Furthermore, we report experimental results on selected problems. Our experience is encouraging that answer set planning may be a valuable approach to expressive planning systems in which intricate planning problems can be naturally specified and solved.

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