Planning with Different Forms of Domain-Dependent Control Knowledge — An Answer Set Programming Approach

Author(s):  
Tran Cao Son ◽  
Chitta Baral ◽  
Sheila McIlraith
Author(s):  
Tuomo Lehtonen ◽  
Johannes P. Wallner ◽  
Matti Järvisalo

A major research direction in AI argumentation is the study and development of practical computational techniques for reasoning in different argumentation formalisms. Compared to abstract argumentation, developing algorithmic techniques for different structured argumentation formalisms, such as assumption-based argumentation and the general ASPIC+ framework, is more challenging. At present, there is a lack of efficient approaches to reasoning in ASPIC+. We develop a direct declarative approach based on answer set programming (ASP) to reasoning in an instantiation of the ASPIC+ framework. We establish formal foundations for direct declarative encodings for reasoning in ASPIC+ without preferences for several central argumentation semantics, and detail ASP encodings of semantics for which reasoning about acceptance is NP-hard in ASPIC+. Empirically, the ASP approach scales up to frameworks of significant size, thereby answering the current lack of practical computational approaches to reasoning in ASPIC+ and providing a promising base for capturing further generalizations within ASPIC+.


2015 ◽  
Vol 64 ◽  
pp. 54-74 ◽  
Author(s):  
Esteban Guerrero ◽  
Juan Carlos Nieves ◽  
Helena Lindgren

2020 ◽  
Vol 20 (6) ◽  
pp. 1006-1020
Author(s):  
Momina Rizwan ◽  
Volkan Patoglu ◽  
Esra Erdem

AbstractFor planning an assembly of a product from a given set of parts, robots necessitate certain cognitive skills: high-level planning is needed to decide the order of actuation actions, while geometric reasoning is needed to check the feasibility of these actions. For collaborative assembly tasks with humans, robots require further cognitive capabilities, such as commonsense reasoning, sensing, and communication skills, not only to cope with the uncertainty caused by incomplete knowledge about the humans’ behaviors but also to ensure safer collaborations. We propose a novel method for collaborative assembly planning under uncertainty, that utilizes hybrid conditional planning extended with commonsense reasoning and a rich set of communication actions for collaborative tasks. Our method is based on answer set programming. We show the applicability of our approach in a real-world assembly domain, where a bi-manual Baxter robot collaborates with a human teammate to assemble furniture.


2017 ◽  
Vol 17 (5-6) ◽  
pp. 800-818 ◽  
Author(s):  
MARCO GAVANELLI ◽  
MADDALENA NONATO ◽  
ANDREA PEANO ◽  
DAVIDE BERTOZZI

AbstractOne promising trend in digital system integration consists of boosting on-chip communication performance by means of silicon photonics, thus materializing the so-called Optical Networks-on-Chip. Among them, wavelength routing can be used to route a signal to destination by univocally associating a routing path to the wavelength of the optical carrier. Such wavelengths should be chosen so to minimize interferences among optical channels and to avoid routing faults. As a result, physical parameter selection of such networks requires the solution of complex constrained optimization problems. In previous work, published in the proceedings of the International Conference on Computer-Aided Design, we proposed and solved the problem of computing the maximum parallelism obtainable in the communication between any two endpoints while avoiding misrouting of optical signals. The underlying technology, only quickly mentioned in that paper, is Answer Set Programming. In this work, we detail the Answer Set Programming approach we used to solve such problem.Another important design issue is to select the wavelengths of optical carriers such that they are spread across the available spectrum, in order to reduce the likelihood that, due to imperfections in the manufacturing process, unintended routing faults arise. We show how to address such problem in Constraint Logic Programming on Finite Domains.


2008 ◽  
Vol 9 (4) ◽  
pp. 1-53 ◽  
Author(s):  
Stijn Heymans ◽  
Davy Van Nieuwenborgh ◽  
Dirk Vermeir

Sign in / Sign up

Export Citation Format

Share Document