D-Index & Metrics Best Publications
Georgios N. Yannakakis

Georgios N. Yannakakis

D-Index & Metrics 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.

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 56 Citations 10,943 269 World Ranking 2717 National Ranking 1

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Statistics

His primary areas of investigation include Artificial intelligence, Human–computer interaction, Game mechanics, Game design and Preference learning. His Artificial intelligence research is multidisciplinary, incorporating perspectives in Machine learning and Entertainment. His studies deal with areas such as User interface, Multimedia, Novelty and Computer-aided as well as Human–computer interaction.

His study in the field of Video game design is also linked to topics like sort and Navigation mesh. His study looks at the relationship between Game design and fields such as Creativity, as well as how they intersect with chemical problems. His Preference learning research is multidisciplinary, incorporating elements of Affective computing, Frustration and Pairwise comparison.

His most cited work include:

  • Search-Based Procedural Content Generation: A Taxonomy and Survey (472 citations)
  • Experience-Driven Procedural Content Generation (310 citations)
  • Player modeling using self-organization in Tomb Raider: Underworld (210 citations)

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

Georgios N. Yannakakis mainly investigates Artificial intelligence, Human–computer interaction, Multimedia, Game design and Machine learning. His study in Preference learning extends to Artificial intelligence with its themes. His work deals with themes such as Scheme and Creativity, which intersect with Human–computer interaction.

His study in Multimedia is interdisciplinary in nature, drawing from both Field and Entertainment. His research in the fields of Game design document and Game Developer overlaps with other disciplines such as Non-cooperative game and Simultaneous game. His Machine learning research includes themes of Novelty, Surprise, Robustness and Search algorithm.

He most often published in these fields:

  • Artificial intelligence (41.90%)
  • Human–computer interaction (26.76%)
  • Multimedia (18.66%)

What were the highlights of his more recent work (between 2017-2021)?

  • Human–computer interaction (26.76%)
  • Artificial intelligence (41.90%)
  • Affect (8.45%)

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

His main research concerns Human–computer interaction, Artificial intelligence, Affect, Deep learning and Cognitive psychology. His Human–computer interaction research includes elements of Domain, Observer, Preference learning and Cognitive reframing. His Artificial intelligence research incorporates elements of Field, Machine learning and Novelty.

The concepts of his Field study are interwoven with issues in Multimedia, Ai education and Computational thinking. His work on Game design as part of general Multimedia research is often related to Content generation and Computational Science and Engineering, thus linking different fields of science. His research integrates issues of Annotation, Key and Perception in his study of Affect.

Between 2017 and 2021, his most popular works were:

  • Artificial Intelligence and Games (76 citations)
  • Procedural Content Generation through Quality Diversity (33 citations)
  • The Ordinal Nature of Emotions: An Emerging Approach (29 citations)

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

  • Artificial intelligence
  • Machine learning
  • Statistics

Georgios N. Yannakakis mainly focuses on Artificial intelligence, Deep learning, Affective computing, Human–computer interaction and Task analysis. He regularly ties together related areas like Machine learning in his Artificial intelligence studies. His studies in Machine learning integrate themes in fields like Novelty, Surprise and Robustness.

Georgios N. Yannakakis has included themes like Game design, Multimedia, Field and Surrogate model in his Deep learning study. His Affective computing study integrates concerns from other disciplines, such as Cognitive psychology, Key and Preference learning. His Human–computer interaction research is multidisciplinary, relying on both Domain, Valence, Crowdsourcing and Affect.

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

Search-Based Procedural Content Generation: A Taxonomy and Survey

J. Togelius;G. N. Yannakakis;K. O. Stanley;C. Browne.
IEEE Transactions on Computational Intelligence and AI in Games (2011)

771 Citations

Experience-Driven Procedural Content Generation

G. N. Yannakakis;J. Togelius.
IEEE Transactions on Affective Computing (2011)

520 Citations

Artificial Intelligence and Games

Georgios N. Yannakakis;Julian Togelius.
(2018)

401 Citations

Correlation between heart rate, electrodermal activity and player experience in first-person shooter games

Anders Drachen;Lennart E. Nacke;Georgios Yannakakis;Anja Lee Pedersen.
international conference on computer graphics and interactive techniques (2010)

343 Citations

Player modeling using self-organization in Tomb Raider: Underworld

Anders Drachen;Alessandro Canossa;Georgios N. Yannakakis.
computational intelligence and games (2009)

324 Citations

Learning deep physiological models of affect

Hector P. Martinez;Yoshua Bengio;Georgios N. Yannakakis.
IEEE Computational Intelligence Magazine (2013)

292 Citations

Modeling Player Experience for Content Creation

C. Pedersen;J. Togelius;G.N. Yannakakis.
IEEE Transactions on Computational Intelligence and AI in Games (2010)

285 Citations

Towards automatic personalized content generation for platform games

Noor Shaker;Georgios Yannakakis;Julian Togelius.
national conference on artificial intelligence (2010)

271 Citations

Real-Time Game Adaptation for Optimizing Player Satisfaction

G.N. Yannakakis;J. Hallam.
computational intelligence and games (2009)

233 Citations

Sentient sketchbook : computer-assisted game level authoring

Antonios Liapis;Georgios N. Yannakakis;Julian Togelius.
foundations of digital games (2013)

233 Citations

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