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Vedavyas Etikala

Vedavyas Etikala
KU Leuven | ku leuven · Department of Decision Sciences and Information Management

PhD in Business Economics.

About

9
Publications
1,423
Reads
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11
Citations
Introduction
Vedavyas Etikala} is a Ph.D. student in the Faculty of Economics and Business, KU Leuven where he started his research at Research Centre for Information Systems Engineering (LIRIS) in the Department of Decision Sciences and Information Management. His research interests focus on the application of Knowledge-based Artificial Intelligence (KBAI) technologies for decision making in information systems, with specific emphasis on the knowledge representation and reasoning, and decision modeling.
Additional affiliations
July 2014 - present
Indian Institute of Technology Madras
Position
  • Research Assistant
Description
  • Courses: Artificial Intelligence; Knowledge Representation and Reasoning. Labs: Advanced Programming Lab and Computer Programming lab.
Education
July 2014 - May 2016
Indian Institute of Technology Madras
Field of study
  • Computer Science

Publications

Publications (9)
Conference Paper
Full-text available
Digital transformation is a popular research topic about the broad changes happening in business due to the increased impact of digital technologies. While the academic attention is high, the importance of decision management is underresearched. In this paper, we elaborate on how decision modeling can aid companies in the digital transformation of...
Chapter
Decision models are the consolidated knowledge representation of the requirements and the logic of operational decisions in business organizations. Decision models defined in the Decision Model and Notation (DMN) standard can contribute significantly to the automation of business decision management. However, the current scope of decision support i...
Presentation
Full-text available
The goal of e�ective decision modeling is to store, process, and execute veri�able decision knowledge in an organization. Decision knowledge when modeled as per Decision Model and Notation (DMN) standard increases the interpretability of that decision. E�ective and explainable communication of the decision-making process based on de- cision models...
Chapter
Full-text available
Decisions are of significant value to organizations. Furthermore, these business decisions are often represented in various knowledge sources, and manually modeling them is costly, tedious, and time-consuming. As decision modeling has seen a surge of interest since the introduction of the Decision Model and Notation (DMN) standard, research interes...
Conference Paper
Full-text available
Digital transformation is the rapidly expanding research field dealing with the increased impact of digital technologies on both business and society. Due to the large number of papers and the semantic ambiguity surrounding the terminology, covering such a broad topic is difficult. To help researchers gain a better understanding of the knowledge st...
Conference Paper
Full-text available
Decisions are of significant value to organisations. Business decisions are often written down in textual documents, and modelling them is a tedious and time-consuming task. Although decision modelling has seen a surge of interest since the introduction of the Decision Model and Notation (DMN) standard, limited research has been conducted regarding...
Chapter
Decision Model and Notation (DMN) models are user-friendly representations of decision logic. While the knowledge in the model could be used for multiple purposes, current DMN tools typically only support a single form of inference. We present DMN-IDPy, a novel Python API that links DMN as a notation to the IDP system, a powerful reasoning tool, al...
Preprint
Decisions are of significant value to organisations. Business decisions are often written down in textual documents, and modelling them is a tedious and time-consuming task. Although decision modelling has seen a surge of interest since the introduction of the Decision Model and Notation (DMN) standard, limited research has been conducted regarding...
Thesis
Full-text available
In the real world systems, even when uncertainty plays an antagonist role, natural intelligent systems tend to be robust, whereas artificial intelligent systems tend to be frail. Often humans might not behave optimally but are able to reason out a good solution for any uncertain problem. An ideal example would be expert level reasoning in the imper...

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Projects

Projects (2)
Project
Modelling and automating business processes, along with decisions, are essential for improving efficiency and effectiveness in businesses. This PhD work focus will be on working on methods to automate modelling and also on the integration of process and decisions models using Decision Model and Notation (DMN) standard. The research project is funded by the Fund for Scientific Research Flanders (FWO).
Archived project
Metacognition is an area of Artificial Intelligence that focuses on studying and simulating high-level cognition of natural intelligent systems. We are currently investigating a novel metareasoning system built over Soar cognitive architecture that monitors and controls an agent's existing reasoning system in order to boost accuracy in problem-solving tasks across a variety of domains of imperfect information. This metareasoning system allows artificial cognitive agents to be “self-reflective” and, in some cases, fix their mistakes.