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[PDF] Top 20 Representing and Learning Grammars in Answer Set Programming

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Representing and Learning Grammars in Answer Set Programming

Representing and Learning Grammars in Answer Set Programming

... by representing each constraint : - body as the rule vio : - body (where vio is a new atom that in- dicates that at least one constraint has been ...unique answer set of the (stratified) pro- gram ... See full document

10

Planning in answer set programming while learning action costs for mobile robots

Planning in answer set programming while learning action costs for mobile robots

... Automated planning provides great flexibility over direct implementation of behaviors for robotic tasks. In mobile robotics, uncertainty about the environment stems from many sources. This is particularly true for ... See full document

9

Visual Reasoning on Complex Events in Soccer Videos Using Answer Set Programming

Visual Reasoning on Complex Events in Soccer Videos Using Answer Set Programming

... Event Calculus. Event Calculus (EC) was first introduced by Kowalski and Sergot in [22] as a logic framework for representing and reasoning about events and their effects. EC has been frequently used for event ... See full document

12

PP 2019 21: 
  Answer Set Programming for Judgment Aggregation

PP 2019 21: Answer Set Programming for Judgment Aggregation

... modern answer set solvers and be- cause they allow for several aggregation problems to be imple- mented by representing them as judgment aggregation prob- ...of answer set im- ... See full document

7

Semantics and complexity of recursive aggregates in answer set programming

Semantics and complexity of recursive aggregates in answer set programming

... formula representing an aggregate not satisfied by I will be completely replaced by ⊥ (falsity), rendering the corresponding rule irrelevant in the ...formula representing an aggregate satisfied by I will ... See full document

39

State Aggregation through Reasoning in Answer Set Programming

State Aggregation through Reasoning in Answer Set Programming

... Answer set programming allows us to write very compact models, and the answer set solver clingo can return not just one plan but all plans that fulfill certain constraints, which will ... See full document

8

ON MODELING TRACES IN A COMPUTING ENVIRONMENT FOR HUMAN LEARNING BASED 
INDICATORS

ON MODELING TRACES IN A COMPUTING ENVIRONMENT FOR HUMAN LEARNING BASED INDICATORS

... in Answer Set Programming (ASP), a fully declarative language for Knowledge Representation and ...logic programming and nonmonotonic reasoning, and has been already exploited for solving ... See full document

7

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

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

... machine learning (ML) based ap- proaches have been the popular approach in developing end- to-end question answering systems, such systems often strug- gle when additional knowledge is needed to correctly an- swer ... See full document

8

Learning Computational Grammars

Learning Computational Grammars

... Logic Programming (ILP) Aleph is an ILP machine learning system that searches for a hypothesis, given positive (and, if avail- able, negative) data in the form of ground Prolog terms and background ... See full document

8

Enhancing Lazy Grounding with Lazy Normalization in Answer-Set Programming

Enhancing Lazy Grounding with Lazy Normalization in Answer-Set Programming

... because they are highly expressive and enable a program- mer to state complex conditions in a very concise manner. The importance of aggregates is witnessed by a rich body of research, see e.g., (Greco 1999; Simons, ... See full document

9

Designing views to answer queries under set, bag, and bag-set semantics

Designing views to answer queries under set, bag, and bag-set semantics

... Some results in this paper are given for a special type of constraints L on materialized views: In those results, L is a singleton set L = {C}, C ² N. The storage-limit C means that the total size size(V(D)) of ... See full document

6

Measuring the Effectiveness of Teaching and Learning Programming Through Embedded Systems

Measuring the Effectiveness of Teaching and Learning Programming Through Embedded Systems

... teach programming to school children in Malaysia. Embedded Systems Programming (ESP) module is a module which was developed by adapting teaching methods that are based on embedded systems and robotic as it ... See full document

10

Joint Bayesian Morphology Learning for Dravidian Languages

Joint Bayesian Morphology Learning for Dravidian Languages

... ogy learning technique that uses statistical mea- sures and linguistic ...Adaptor Grammars in the case of complex Indian languages and showed that it can be used in languages with complex mor- phology and ... See full document

7

Representing and Querying Multiple Ontologies with Contextual Logic Programming

Representing and Querying Multiple Ontologies with Contextual Logic Programming

... Declarative Programming languages and applications, with a focus on Logic and Constraint programming as well as efficient and transparent parallel program ... See full document

24

Query Answering With Non-Monotonic Rules: A Case Study of Archaeology Qualitative Spatial Reasoning

Query Answering With Non-Monotonic Rules: A Case Study of Archaeology Qualitative Spatial Reasoning

... to measure and identify them. One of the main advantage of the photogrammetric process is to pro- vide several 2D representations of the measured artifacts. This first ontology is built from an existing JAVA code in ... See full document

14

Repurposing Entailment for Multi Hop Question Answering Tasks

Repurposing Entailment for Multi Hop Question Answering Tasks

... Question Answering (QA) naturally reduces to an entailment problem, namely, verifying whether some text entails the answer to a ques- tion. However, for multi-hop QA tasks, which require reasoning with multiple ... See full document

11

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... context-free grammars and attribute grammars that enable the specification of binary file formats are ...of grammars are then ...string grammars, in ... See full document

12

Learning and Application of Differential Grammars

Learning and Application of Differential Grammars

... This work was undertaken jointly with Philip Kernick who, in particular, implemented the user interfaces and carried out the exlferiments whose results are reported in Table 1 as part of[r] ... See full document

9

Learning Stochastic Categorial Grammars

Learning Stochastic Categorial Grammars

... Also, our learner used virtually no supervision for example parsed corpora, and did not start with a given lexicon: learning using parsed corpora is substantiMly easier than learning fro[r] ... See full document

8

Learning Knowledge Graphs for Question Answering through Conversational Dialog

Learning Knowledge Graphs for Question Answering through Conversational Dialog

... correct answer. For example, our ques- tion set contains a single math problem, How long does it take for Earth to rotate on its axis seven times? (A) one day (B) one week (C) one month (D) one ...the ... See full document

11

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