D-Index & Metrics Best Publications

D-Index & Metrics

Discipline name D-index D-index (Discipline H-index) only includes papers and citation values for an examined discipline in contrast to General H-index which accounts for publications across all disciplines. Citations Publications World Ranking National Ranking
Computer Science D-index 31 Citations 5,714 135 World Ranking 7837 National Ranking 227

Overview

What is she best known for?

The fields of study she is best known for:

  • Programming language
  • Artificial intelligence
  • Software

Lin Padgham mostly deals with Intelligent agent, Software engineering, Plan, Systems engineering and Agent architecture. Intelligent agent is a subfield of Artificial intelligence that Lin Padgham studies. The concepts of her Software engineering study are interwoven with issues in Debugger, Petri net and Knowledge management.

Her Plan research incorporates elements of Programming language, Formal semantics, Executable and Real-time computing. Her Systems engineering research is multidisciplinary, incorporating perspectives in Agent oriented software and Agent-oriented software engineering. Her Agent architecture research focuses on Software development and how it connects with Deliverable and Iterative and incremental development.

Her most cited work include:

  • Developing Intelligent Agent Systems: A Practical Guide (476 citations)
  • Prometheus: a methodology for developing intelligent agents (249 citations)
  • Declarative and procedural goals in intelligent agent systems (205 citations)

What are the main themes of her work throughout her whole career to date?

The scientist’s investigation covers issues in Artificial intelligence, Software engineering, Intelligent agent, Knowledge management and Multi-agent system. Her Artificial intelligence research is multidisciplinary, relying on both Theoretical computer science, Inheritance, Plan, Set and Machine learning. Her Software engineering research includes themes of Software development, Agent-oriented software engineering and Systems engineering.

Her work carried out in the field of Intelligent agent brings together such families of science as Software, Unit testing and Risk analysis. Her Knowledge management study integrates concerns from other disciplines, such as Agent-based social simulation, Resource, The Internet and Belief desire intention. Lin Padgham works mostly in the field of Multi-agent system, limiting it down to topics relating to Distributed computing and, in certain cases, Key, as a part of the same area of interest.

She most often published in these fields:

  • Artificial intelligence (26.76%)
  • Software engineering (23.00%)
  • Intelligent agent (17.37%)

What were the highlights of her more recent work (between 2011-2019)?

  • Artificial intelligence (26.76%)
  • Knowledge management (16.90%)
  • Belief desire intention (5.16%)

In recent papers she was focusing on the following fields of study:

Her primary scientific interests are in Artificial intelligence, Knowledge management, Belief desire intention, Key and Plan. Her Artificial intelligence research is multidisciplinary, incorporating elements of Construct and Natural language processing. Her Knowledge management study combines topics in areas such as Multi-agent system, Programming paradigm, Human–computer interaction and Embodied cognition.

Lin Padgham has included themes like Intelligent agent, Boolean data type and Variable in her Plan study. In her research on the topic of Intelligent agent, Programmer is strongly related with Point. Her Management science research incorporates elements of Software engineering and Modular design.

Between 2011 and 2019, her most popular works were:

  • Reframing social sustainability reporting: towards an engaged approach (78 citations)
  • Model-Based Test Oracle Generation for Automated Unit Testing of Agent Systems (49 citations)
  • Integrating BDI Agents with Agent-Based Simulation Platforms (32 citations)

In her most recent research, the most cited papers focused on:

  • Artificial intelligence
  • Programming language
  • Software

Her main research concerns Artificial intelligence, Modular design, Knowledge management, Distributed computing and Set. Her work deals with themes such as Construct and Natural language processing, which intersect with Artificial intelligence. Her work carried out in the field of Modular design brings together such families of science as Event, Key and Systems engineering.

Her Knowledge management research includes themes of Semantics, Autonomous agent and Plan library. Her research in Distributed computing intersects with topics in Multi-agent system and Simulation. Her studies in Set integrate themes in fields like Intelligent agent, Machine learning, Variation and Point.

This overview was generated by a machine learning system which analysed the scientist’s body of work. If you have any feedback, you can contact us here.

Best Publications

Developing Intelligent Agent Systems: A Practical Guide

Lin Padgham;Michael Winikoff.
(2004)

934 Citations

Prometheus: a methodology for developing intelligent agents

Lin Padgham;Michael Winikoff.
AOSE'02 Proceedings of the 3rd international conference on Agent-oriented software engineering III (2002)

764 Citations

Declarative and procedural goals in intelligent agent systems

Michael Winikoff;Lin Padgham;James Harland;John Thangarajah.
principles of knowledge representation and reasoning (2002)

259 Citations

Reframing social sustainability reporting: towards an engaged approach

Liam Magee;Andy Scerri;Paul James;James A. Thom.
Environment, Development and Sustainability (2013)

216 Citations

Hierarchical planning in BDI agent programming languages: a formal approach

Sebastian Sardina;Lavindra de Silva;Lin Padgham.
adaptive agents and multi-agents systems (2006)

161 Citations

Detecting & avoiding interference between goals in intelligent agents

John Thangarajah;Lin Padgham;Michael Winikoff.
international joint conference on artificial intelligence (2003)

147 Citations

Debugging multi-agent systems using design artifacts: the case of interaction protocols

David Poutakidis;Lin Padgham;Michael Winikoff.
adaptive agents and multi-agents systems (2002)

141 Citations

Prometheus: A Pragmatic Methodology for Engineering Intelligent Agents

Lin Padgham;Michael Winikoff.
(2002)

138 Citations

A BDI agent programming language with failure handling, declarative goals, and planning

Sebastian Sardina;Lin Padgham.
Autonomous Agents and Multi-Agent Systems (2011)

110 Citations

Non-monotonic inheritance for an object-oriented knowledge-base

Lin Padgham.
(1989)

107 Citations

Best Scientists Citing Lin Padgham

Michael Winikoff

Michael Winikoff

Victoria University of Wellington

Publications: 60

Mehdi Dastani

Mehdi Dastani

Utrecht University

Publications: 33

Leon Sterling

Leon Sterling

Swinburne University of Technology

Publications: 30

Koen V. Hindriks

Koen V. Hindriks

Vrije Universiteit Amsterdam

Publications: 24

Antonio Fernández-Caballero

Antonio Fernández-Caballero

University of Castilla-La Mancha

Publications: 23

Rafael H. Bordini

Rafael H. Bordini

Pontifical Catholic University of Rio Grande do Sul

Publications: 23

John-Jules Ch. Meyer

John-Jules Ch. Meyer

Utrecht University

Publications: 22

Anna Perini

Anna Perini

Fondazione Bruno Kessler

Publications: 20

Brian Henderson-Sellers

Brian Henderson-Sellers

University of Technology Sydney

Publications: 18

Catholijn M. Jonker

Catholijn M. Jonker

Delft University of Technology

Publications: 18

Alessandro Ricci

Alessandro Ricci

University of Bologna

Publications: 17

Munindar P. Singh

Munindar P. Singh

North Carolina State University

Publications: 15

Michael Luck

Michael Luck

King's College London

Publications: 14

Carlos José Pereira de Lucena

Carlos José Pereira de Lucena

Pontifical Catholic University of Rio de Janeiro

Publications: 13

Winfried Lamersdorf

Winfried Lamersdorf

Universität Hamburg

Publications: 13

Virginia Dignum

Virginia Dignum

Umeå University

Publications: 12

Profile was last updated on December 6th, 2021.
Research.com Ranking is based on data retrieved from the Microsoft Academic Graph (MAG).
The ranking d-index is inferred from publications deemed to belong to the considered discipline.

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