scholarly journals Advanced Knowledge Representation and Reasoning Making Use of an Advanced N-ary Model

2019 ◽  
pp. 1-22
Author(s):  
Gian Zarri
Keyword(s):  
Knowledge Representation ◽  
Causal Reasoning ◽  
Formal Model ◽  
Knowledge Representation And Reasoning ◽  
Conceptual Tool ◽  
Complex Events ◽  
Knowledge Representation Language ◽  
Advanced Knowledge ◽  
Representation Language ◽  
High Level

We discuss in this paper some aspects of NKRL, the Narrative Knowledge Representation Language. This is a high-level n-ary conceptual tool specially conceived for the representation and management of real world, dynamically characterized entities like situations, events and complex events, actions (e.g., in a robotics context) scripts/scenarios/narratives etc. After having pointed out some shortcomings of the standard ontological solutions for dealing with this sort of information, and having recalled some general characteristics of NKRL (like the addition of an "ontology of events" to the usual "ontology of objects"), we focus on the rules/inferential aspects proper to this language. We introduce, then, the general, formal model of "rule" used in an NKRL context and we show how this can be appropriately adapted to the setup of advanced types of inference operations based, e.g., on "analogical" and "causal" reasoning.

Using Rules in the Narrative Knowledge Representation Language (NKRL) Environment

2010 ◽  
pp. 50-75 ◽  
Author(s):  
Gian Piero Zarri
Keyword(s):  
Knowledge Representation ◽  
Analogical Reasoning ◽  
Point Of View ◽  
Inference Rules ◽  
Economic Interest ◽  
Formal Representation ◽  
Representation Point ◽  
Knowledge Representation Language ◽  
Representation Language ◽  
High Level

NKRL is a semantic language expressly designed to deal with all sort of ‘narratives’, in particular with those (‘non-fictional narratives’) of an economic interest. From a knowledge representation point of view, its main characteristics consists in the use of two different sorts of ontologies, a standard, binary ontology of concepts, and an ontology of n-ary templates, where each template corresponds to the formal representation of a class of elementary events. Rules in NKRL correspond to high-level reasoning paradigms like the search for causal relationships or the use of analogical reasoning. Given i) the conceptual complexity of these paradigms, and ii) the sophistication of the underlying representation language, rules in NKRL cannot be implemented in a (weak) ‘inference by inheritance’ style but must follow a powerful ‘inference by resolution’ approach. After a short reminder about these two inference styles, and a quick introduction of the NKRL language, the chapter describes in some depth the main characteristics of the NKRL inference rules.

scholarly journals NKRL, a knowledge representation tool for encoding the ‘meaning’ of complex narrative texts

1997 ◽  
Vol 3 (2) ◽  
pp. 231-253 ◽  
Author(s):  
GIAN PIERO ZARRI
Keyword(s):  
Knowledge Representation ◽  
Data Structures ◽  
Semantic Content ◽  
Narrative Texts ◽  
Knowledge Representation Language ◽  
Representation Language ◽  
Original Narrative

In this paper, we describe NKRL (Narrative Knowledge Representation Language), a language designed for representing, in a standardized way, the semantic content (the ‘meaning’) of complex narrative texts. After having introduced informally the four ‘components’ (specialized sub-languages) of NKRL, we will describe (some of) the data structures proper to each of them, trying to show that the NKRL coding retains the main informational elements of the original narrative expressions. We will then focus on an important subset of NKRL, the so-called AECS sub-language, showing in particular that the operators of this sub-language can be used to represent some sorts of ‘plural’ expressions.

scholarly journals Vicious Circle Principle and Logic Programs with Aggregates

2014 ◽  
Vol 14 (4-5) ◽  
pp. 587-601 ◽  
Author(s):  
MICHAEL GELFOND ◽  
YUANLIN ZHANG
Keyword(s):  
Knowledge Representation ◽  
Vicious Circle ◽  
Logic Programs ◽  
Vicious Circle Principle ◽  
Knowledge Representation Language ◽  
Representation Language ◽  
Answer Sets ◽  
Mathematical Semantics

AbstractThe paper presents a knowledge representation language $\mathcal{A}log$ which extends ASP with aggregates. The goal is to have a language based on simple syntax and clear intuitive and mathematical semantics. We give some properties of $\mathcal{A}log$, an algorithm for computing its answer sets, and comparison with other approaches.

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