no code implementations • 18 Mar 2024 • Roland Kaminski, Torsten Schaub, Tran Cao Son, Jiří Švancara, Philipp Wanko
We present alternative approaches to routing and scheduling in Answer Set Programming (ASP), and explore them in the context of Multi-agent Path Finding.
1 code implementation • 30 Aug 2023 • Mario Alviano, Ly Ly Trieu, Tran Cao Son, Marcello Balduccini
Different from xASP, the new system, xASP2, supports different clingo constructs like the choice rules, the constraints, and the aggregates such as #sum, #min.
no code implementations • 26 Jun 2023 • Stylianos Loukas Vasileiou, Ashwin Kumar, William Yeoh, Tran Cao Son, Francesca Toni
We present DR-HAI -- a novel argumentation-based framework designed to extend model reconciliation approaches, commonly used in human-aware planning, for enhanced human-AI interaction.
1 code implementation • 24 May 2023 • Trung Hoang Le, Huiping Cao, Tran Cao Son
The results show that our ASPER model consistently outperforms the baselines.
no code implementations • 5 Aug 2022 • Ho Tuan Dung, Tran Cao Son
The Model Reconciliation Problem (MRP) was introduced to address issues in explainable AI planning.
no code implementations • 11 Feb 2022 • Tran Cao Son, Enrico Pontelli, Marcello Balduccini, Torsten Schaub
Answer Set Planning refers to the use of Answer Set Programming (ASP) to compute plans, i. e., solutions to planning problems, that transform a given state of the world to another state.
1 code implementation • 14 Jan 2022 • Thanh Hai Nguyen, Matthew Bundas, Tran Cao Son, Marcello Balduccini, Kathleen Campbell Garwood, Edward R. Griffor
This paper introduces a formal definition of a Cyber-Physical System (CPS) in the spirit of the CPS Framework proposed by the National Institute of Standards and Technology (NIST).
no code implementations • 17 Sep 2021 • Ly Ly Trieu, Tran Cao Son, Marcello Balduccini
We present an enhancement of exp(ASP), a system that generates explanation graphs for a literal l - an atom a or its default negation ~a - given an answer set A of a normal logic program P, which explain why l is true (or false) given A and P. The new system, exp(ASPc), differs from exp(ASP) in that it supports choice rules and utilizes constraint rules to provide explanation graphs that include information about choices and constraints.
1 code implementation • 13 Aug 2021 • Jorge Fandinno, François Laferrière, Javier Romero, Torsten Schaub, Tran Cao Son
We present a general approach to planning with incomplete information in Answer Set Programming (ASP).
no code implementations • 18 Apr 2021 • Ly Ly Trieu, Tran Cao Son, Enrico Pontelli, Marcello Balduccini
We present an explanation system for applications that leverage Answer Set Programming (ASP).
no code implementations • 17 Nov 2020 • Stylianos Loukas Vasileiou, William Yeoh, Tran Cao Son
In this paper, we build upon notions from knowledge representation and reasoning (KR) to expand a preliminary logic-based framework that characterizes the model reconciliation problem for explainable planning.
no code implementations • 18 Sep 2019 • Van Duc Nguyen, Tran Cao Son, Enrico Pontelli
It assumes that there exist some natural language sentences in the application domain and uses this repository for the natural language description.
no code implementations • 1 May 2018 • Thanh Hai Nguyen, Enrico Pontelli, Tran Cao Son
The Phylotastic project was launched two years ago as a collaboration between evolutionary biologists and computer scientists, with the goal of developing an open architecture to facilitate the creation of such analysis workflows.
no code implementations • 26 Apr 2018 • Martin Gebser, Philipp Obermeier, Thomas Otto, Torsten Schaub, Orkunt Sabuncu, Van Nguyen, Tran Cao Son
More precisely, asprilo consists of a versatile benchmark generator, solution checker and visualizer as well as a bunch of reference encodings featuring various ASP techniques.
no code implementations • 10 May 2017 • Tiep Le, Tran Cao Son, Enrico Pontelli, William Yeoh
Under consideration in Theory and Practice of Logic Programming (TPLP).
no code implementations • 24 Aug 2016 • Patrick Thor Kahl, Anthony P. Leclerc, Tran Cao Son
As the practical use of answer set programming (ASP) has grown with the development of efficient solvers, we expect a growing interest in extensions of ASP as their semantics stabilize and solvers supporting them mature.
no code implementations • 6 Nov 2015 • Chitta Baral, Gregory Gelfond, Enrico Pontelli, Tran Cao Son
It also allows the specification of agents' dynamic awareness of action occurrences which has future implications on what agents' know about the world and other agents' knowledge about the world.
no code implementations • 7 May 2014 • Tiep Le, Enrico Pontelli, Tran Cao Son, William Yeoh
The field of Distributed Constraint Optimization Problems (DCOPs) has gained momentum, thanks to its suitability in capturing complex problems (e. g., multi-agent coordination and resource allocation problems) that are naturally distributed and cannot be realistically addressed in a centralized manner.
no code implementations • 20 Dec 2013 • Vinay K. Chaudhri, Stijn Heymans, Michael Wessel, Tran Cao Son
Research on developing efficient and scalable ASP solvers can substantially benefit by the availability of data sets to experiment with.