Modeling Natural Language Metaphors with an Answer Set Programming Framework

2014 ◽  
pp. 28-36
Author(s):  
Juan Carlos Acosta-Guadarrama ◽  
Rogelio Dávila-Pérez ◽  
Mauricio Osorio ◽  
Victor Hugo Zaldivar
Keyword(s):  
Natural Language ◽  
Answer Set Programming ◽  
Programming Framework ◽  
Answer Set

CoreALMlib: An library translated from the Component Library

2016 ◽  
Vol 16 (5-6) ◽  
pp. 800-816 ◽  
Author(s):  
DANIELA INCLEZAN
Keyword(s):  
Natural Language ◽  
Answer Set Programming ◽  
Natural Language Understanding ◽  
Inference Engine ◽  
Lexical Resources ◽  
Language Understanding ◽  
Commonsense Knowledge ◽  
Component Library ◽  
Action Language ◽  
Answer Set

AbstractThis paper presents CoreALMlib, an $\mathscr{ALM}$ library of commonsense knowledge about dynamic domains. The library was obtained by translating part of the Component Library (CLib) into the modular action language $\mathscr{ALM}$. CLib consists of general reusable and composable commonsense concepts, selected based on a thorough study of ontological and lexical resources. Our translation targets CLibstates (i.e., fluents) and actions. The resulting $\mathscr{ALM}$ library contains the descriptions of 123 action classes grouped into 43 reusable modules that are organized into a hierarchy. It is made available online and of interest to researchers in the action language, answer-set programming, and natural language understanding communities. We believe that our translation has two main advantages over its CLib counterpart: (i) it specifies axioms about actions in a more elaboration tolerant and readable way, and (ii) it can be seamlessly integrated with ASP reasoning algorithms (e.g., for planning and postdiction). In contrast, axioms are described in CLib using STRIPS-like operators, and CLib's inference engine cannot handle planning nor postdiction.

An Answer Set Programming Framework for Reasoning about Agents' Beliefs and Truthfulness of Statements

2020 ◽  
Author(s):  
Marcello Balduccini ◽  
Michael Gelfond ◽  
Enrico Pontelli ◽  
Tran Cao Son
Keyword(s):  
Answer Set Programming ◽  
Cyber Physical Systems ◽  
Belief State ◽  
Third Party ◽  
Default Reasoning ◽  
Physical Systems ◽  
Reasoning About Actions ◽  
Programming Framework ◽  
Man In The Middle ◽  
Answer Set

The paper proposes a framework for capturing how an agent’s beliefs evolve over time in response to observations and for answering the question of whether statements made by a third party can be believed. The basic components of the framework are a formalism for reasoning about actions, changes, and observations and a formalism for default reasoning. The paper describes a concrete implementation that leverages answer set programming for determining the evolution of an agent's ``belief state'', based on observations, knowledge about the effects of actions, and a theory about how these influence an agent's beliefs. The beliefs are then used to assess whether statements made by a third party can be accepted as truthful. The paper investigates an application of the proposed framework in the detection of man-in-the-middle attacks targeting computers and cyber-physical systems. Finally, we briefly discuss related work and possible extensions.

STRATEGIES TO DEFEND A PROTAGONIST OF AN EVENT

2010 ◽  
Vol 19 (04) ◽  
pp. 439-464
Author(s):  
SARA BOUTOUHAMI ◽  
DANIEL KAYSER
Keyword(s):  
Natural Language ◽  
Experimental Validation ◽  
Answer Set Programming ◽  
First Order ◽  
Starting Point ◽  
First Results ◽  
Argumentative Strategies ◽  
Complete Set ◽  
Car Accident ◽  
Answer Set

We aim at controlling the biases that exist in every description, in order to give the best possible image of one of the protagonists of an event. Starting from a supposedly complete set of propositions accounting for an event, we develop various argumentative strategies (insinuation, justification, reference to customary norms) to imply the facts that cannot be simply omitted but have the "wrong" orientation w.r.t. the protagonist we defend. By analyzing these different strategies, a contribution of this work is to provide a number of relevant parameters to take into account in developing and evaluating systems aiming at understanding natural language (NL) argumentations. The source of inspiration for this work is a corpus of 160 texts where each text describes a (different) car accident. Its result, for a given accident, is a set of first-order literals representing the essential facts of a description intended to defend one of the protagonists. An implementation in Answer Set Programming is underway. A couple of examples showing how to extract, from the same starting point, a defense for the two opposite sides are provided. Experimental validation of this work is in progress, and its first results are reported.

scholarly journals Possibilistic ASP Base Revision by Certain Input

2018 ◽  
Author(s):  
Laurent Garcia ◽  
Claire Lefèvre ◽  
Odile Papini ◽  
Igor Stéphan ◽  
Eric Würbel
Keyword(s):  
Answer Set Programming ◽  
Semantic Content ◽  
Logic Programs ◽  
Rule Based ◽  
Belief Base ◽  
Programming Framework ◽  
Base Revision ◽  
Possibilistic Logic ◽  
Answer Set Semantics ◽  
Answer Set

Belief base revision has been studied within the answer set programming framework. We go a step further by introducing uncertainty and studying belief base revision when beliefs are represented by possibilistic logic programs under possibilistic answer set semantics and revised by certain input. The paper proposes two approaches of rule-based revision operators and presents their semantic characterization in terms of possibilistic distribution. This semantic characterization allows for equivalently considering the evolution of syntactic logic programs and the evolution of their semantic content. It then studies the logical properties of the proposed operators and gives complexity results.

scholarly journals A Trajectory Calculus for Qualitative Spatial Reasoning Using Answer Set Programming

2018 ◽  
Vol 18 (3-4) ◽  
pp. 355-371 ◽  
Author(s):  
GEORGE BARYANNIS ◽  
ILIAS TACHMAZIDIS ◽  
SOTIRIS BATSAKIS ◽  
GRIGORIS ANTONIOU ◽  
MARIO ALVIANO ◽  
...  
Keyword(s):  
Natural Language ◽  
Real World ◽  
Moving Objects ◽  
Spatial Reasoning ◽  
Spatial Information ◽  
Scale Up ◽  
Answer Set Programming ◽  
Qualitative Spatial Reasoning ◽  
Practical Applications ◽  
Answer Set

AbstractSpatial information is often expressed using qualitative terms such as natural language expressions instead of coordinates; reasoning over such terms has several practical applications, such as bus routes planning. Representing and reasoning on trajectories is a specific case of qualitative spatial reasoning that focuses on moving objects and their paths. In this work, we propose two versions of a trajectory calculus based on the allowed properties over trajectories, where trajectories are defined as a sequence of non-overlapping regions of a partitioned map. More specifically, if a given trajectory is allowed to start and finish at the same region, 6 base relations are defined (TC-6). If a given trajectory should have different start and finish regions but cycles are allowed within, 10 base relations are defined (TC-10). Both versions of the calculus are implemented as ASP programs; we propose several different encodings, including a generalised program capable of encoding any qualitative calculus in ASP. All proposed encodings are experimentally evaluated using a real-world dataset. Experiment results show that the best performing implementation can scale up to an input of 250 trajectories for TC-6 and 150 trajectories for TC-10 for the problem of discovering a consistent configuration, a significant improvement compared to previous ASP implementations for similar qualitative spatial and temporal calculi.

scholarly journals Declarative Question Answering over Knowledge Bases Containing Natural Language Text with Answer Set Programming

2019 ◽  
Vol 33 ◽  
pp. 3003-3010 ◽  
Author(s):  
Arindam Mitra ◽  
Peter Clark ◽  
Oyvind Tafjord ◽  
Chitta Baral
Keyword(s):  
Natural Language ◽  
Question Answering ◽  
Answer Set Programming ◽  
Knowledge Bases ◽  
Logical Reasoning ◽  
Natural Language Text ◽  
Question Answering Systems ◽  
Logical Representation ◽  
Language Text ◽  
Answer Set

While in recent years machine learning (ML) based approaches have been the popular approach in developing endto-end question answering systems, such systems often struggle when additional knowledge is needed to correctly answer the questions. Proposed alternatives involve translating the question and the natural language text to a logical representation and then use logical reasoning. However, this alternative falters when the size of the text gets bigger. To address this we propose an approach that does logical reasoning over premises written in natural language text. The proposed method uses recent features of Answer Set Programming (ASP) to call external NLP modules (which may be based on ML) which perform simple textual entailment. To test our approach we develop a corpus based on the life cycle questions and showed that Our system achieves up to 18% performance gain when compared to standard MCQ solvers.

scholarly journals Using Answer Set Programming for Commonsense Reasoning in the Winograd Schema Challenge

2019 ◽  
Vol 19 (5-6) ◽  
pp. 1021-1037
Author(s):  
ARPIT SHARMA
Keyword(s):  
Natural Language ◽  
Answer Set Programming ◽  
Natural Language Understanding ◽  
Turing Test ◽  
Subgraph Isomorphism ◽  
Commonsense Reasoning ◽  
Language Understanding ◽  
Commonsense Knowledge ◽  
Additional Constraints ◽  
Answer Set

AbstractThe Winograd Schema Challenge (WSC) is a natural language understanding task proposed as an alternative to the Turing test in 2011. In this work we attempt to solve WSC problems by reasoning with additional knowledge. By using an approach built on top of graph-subgraph isomorphism encoded using Answer Set Programming (ASP) we were able to handle 240 out of 291 WSC problems. The ASP encoding allows us to add additional constraints in an elaboration tolerant manner. In the process we present a graph based representation of WSC problems as well as relevant commonsense knowledge.

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