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 34 Citations 6,032 163 World Ranking 6401 National Ranking 3076

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • The Internet

Mark O. Riedl mainly investigates Multimedia, Human–computer interaction, Narrative, Artificial intelligence and Storytelling. Mark O. Riedl has included themes like Cinematography and Empirical research in his Multimedia study. His work on Metaverse as part of general Human–computer interaction study is frequently linked to Filter, bridging the gap between disciplines.

His work in the fields of Narrative, such as Plot, overlaps with other areas such as Class. His Natural language study in the realm of Artificial intelligence connects with subjects such as Cognitive load. His work on Narrative criticism expands to the thematically related Storytelling.

His most cited work include:

  • Narrative planning: balancing plot and character (349 citations)
  • An architecture for integrating plan-based behavior generation with interactive game environments. (199 citations)
  • From linear story generation to branching story graphs (184 citations)

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

His primary areas of study are Human–computer interaction, Artificial intelligence, Multimedia, Narrative and Storytelling. His Human–computer interaction research includes themes of Action, Context, Creativity and Reinforcement learning. Mark O. Riedl has researched Artificial intelligence in several fields, including Machine learning and Natural language processing.

Mark O. Riedl focuses mostly in the field of Multimedia, narrowing it down to matters related to Interactive storytelling and, in some cases, Agency. His work deals with themes such as Entertainment, Cognitive science and Plan, which intersect with Narrative. His Game design research is multidisciplinary, incorporating perspectives in Computer game, Space and Game mechanics.

He most often published in these fields:

  • Human–computer interaction (36.56%)
  • Artificial intelligence (28.63%)
  • Multimedia (27.75%)

What were the highlights of his more recent work (between 2018-2021)?

  • Human–computer interaction (36.56%)
  • Artificial intelligence (28.63%)
  • Natural language (11.01%)

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

The scientist’s investigation covers issues in Human–computer interaction, Artificial intelligence, Natural language, Reinforcement learning and Natural language processing. Mark O. Riedl works in the field of Human–computer interaction, focusing on Game design in particular. His Artificial intelligence research includes elements of Transparency and Machine learning.

His Natural language research is multidisciplinary, incorporating elements of State and Knowledge graph. His research on Reinforcement learning also deals with topics like

  • Normative, which have a strong connection to Intelligent agent, Norm and Cognitive psychology,
  • Transfer of learning which connect with Domain knowledge and Knowledge economy. His study in Coherence is interdisciplinary in nature, drawing from both Commonsense reasoning and Storytelling, Narrative.

Between 2018 and 2021, his most popular works were:

  • Automated rationale generation: a technique for explainable AI and its effects on human perceptions (49 citations)
  • Human‐centered artificial intelligence and machine learning (37 citations)
  • Playing Text-Adventure Games with Graph-Based Deep Reinforcement Learning (35 citations)

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

  • Artificial intelligence
  • Machine learning
  • The Internet

His scientific interests lie mostly in Human–computer interaction, Natural language, Artificial intelligence, Reinforcement learning and Action. In general Human–computer interaction study, his work on Level design often relates to the realm of Value, thereby connecting several areas of interest. Mark O. Riedl has researched Natural language in several fields, including Intelligent agent and Norm.

His work carried out in the field of Artificial intelligence brings together such families of science as Transparency and Plot. Plot is a subfield of Narrative that Mark O. Riedl tackles. The Action study combines topics in areas such as Context, Autonomous agent and Perception.

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

Narrative planning: balancing plot and character

Mark O. Riedl;R. Michael Young.
Journal of Artificial Intelligence Research (2010)

621 Citations

An architecture for integrating plan-based behavior generation with interactive game environments.

R. Michael Young;Mark O. Riedl;Mark Branly;Arnav Jhala.
J. Game Dev. (2004)

313 Citations

Managing interaction between users and agents in a multi-agent storytelling environment

Mark Riedl;C. J. Saretto;R. Michael Young.
adaptive agents and multi-agents systems (2003)

281 Citations

From linear story generation to branching story graphs

M.O. Riedl;R.M. Young.
IEEE Computer Graphics and Applications (2006)

269 Citations

Interactive Narrative: An Intelligent Systems Approach

Mark Owen Riedl;Vadim Bulitko.
Ai Magazine (2012)

259 Citations

Story generation with crowdsourced plot graphs

Boyang Li;Stephen Lee-Urban;George Johnston;Mark O. Riedl.
national conference on artificial intelligence (2013)

211 Citations

An Intent-Driven Planner for Multi-Agent Story Generation

Mark Owen Riedl;R. Michael Young.
adaptive agents and multi-agents systems (2004)

209 Citations

Believable agents and intelligent story adaptation for interactive storytelling

Mark O. Riedl;Andrew Stern.
Lecture Notes in Computer Science (2006)

181 Citations

Toward supporting stories with procedurally generated game worlds

Ken Hartsook;Alexander Zook;Sauvik Das;Mark O. Riedl.
computational intelligence and games (2011)

123 Citations

AI for game production

Mark Owen Riedl;Alexander Zook.
computational intelligence and games (2013)

108 Citations

Best Scientists Citing Mark O. Riedl

Julian Togelius

Julian Togelius

New York University

Publications: 51

Michael Mateas

Michael Mateas

University of California, Santa Cruz

Publications: 39

James C. Lester

James C. Lester

North Carolina State University

Publications: 37

Georgios N. Yannakakis

Georgios N. Yannakakis

University of Malta

Publications: 29

Ana Paiva

Ana Paiva

Instituto Superior Técnico

Publications: 16

Kristian J. Hammond

Kristian J. Hammond

Northwestern University

Publications: 16

Lawrence A. Birnbaum

Lawrence A. Birnbaum

Northwestern University

Publications: 15

Stacy Marsella

Stacy Marsella

Northeastern University

Publications: 14

Robert W. Sumner

Robert W. Sumner

ETH Zurich

Publications: 13

Markus Gross

Markus Gross

ETH Zurich

Publications: 11

Yejin Choi

Yejin Choi

Allen Institute for Artificial Intelligence

Publications: 10

Alan W. Black

Alan W. Black

Carnegie Mellon University

Publications: 10

Chunyan Miao

Chunyan Miao

Nanyang Technological University

Publications: 10

Simon Colton

Simon Colton

Queen Mary University of London

Publications: 10

Marilyn A. Walker

Marilyn A. Walker

University of California, Santa Cruz

Publications: 9

David V. Pynadath

David V. Pynadath

University of Southern California

Publications: 8

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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