H-Index & Metrics Top Publications

H-Index & Metrics

Discipline name H-index Citations Publications World Ranking National Ranking
Computer Science H-index 65 Citations 13,973 302 World Ranking 1163 National Ranking 682

Overview

What is he best known for?

The fields of study he is best known for:

  • Artificial intelligence
  • Machine learning
  • Programming language

Julian Togelius focuses on Artificial intelligence, Evolutionary computation, Evolutionary algorithm, Game design and Game mechanics. His research on Artificial intelligence frequently connects to adjacent areas such as Machine learning. His Machine learning research includes themes of Taxonomy, Field, Information retrieval and Search algorithm.

His Evolutionary computation study incorporates themes from Theoretical computer science and Content creation. His Evolutionary algorithm study combines topics in areas such as Fitness function, Pareto principle, Representation, Player experience and Crossover. His study in the fields of Video game design under the domain of Game mechanics overlaps with other disciplines such as Mathematical game.

His most cited work include:

  • Search-Based Procedural Content Generation: A Taxonomy and Survey (472 citations)
  • Experience-Driven Procedural Content Generation (310 citations)
  • Towards automatic personalised content creation for racing games (241 citations)

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

Julian Togelius spends much of his time researching Artificial intelligence, Human–computer interaction, Machine learning, Game design and Evolutionary computation. His work in Artificial intelligence tackles topics such as Video game which are related to areas like Set. Particularly relevant to Level design is his body of work in Human–computer interaction.

His work on Game design document and Game art design as part of general Game design study is frequently linked to Sequential game and Simulations and games in economics education, bridging the gap between disciplines. As a member of one scientific family, Julian Togelius mostly works in the field of Evolutionary computation, focusing on Theoretical computer science and, on occasion, Space. Julian Togelius interconnects Video game development and Game Developer in the investigation of issues within Game mechanics.

He most often published in these fields:

  • Artificial intelligence (47.38%)
  • Human–computer interaction (22.38%)
  • Machine learning (16.43%)

What were the highlights of his more recent work (between 2019-2021)?

  • Artificial intelligence (47.38%)
  • Machine learning (16.43%)
  • Human–computer interaction (22.38%)

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

His primary areas of study are Artificial intelligence, Machine learning, Human–computer interaction, Video game and Content generation. Julian Togelius regularly links together related areas like Domain in his Artificial intelligence studies. His Machine learning research focuses on subjects like Classifier, which are linked to Adversarial system.

Julian Togelius combines subjects such as Theoretical computer science, Game mechanics, Solver, Integer programming and Component with his study of Video game. His studies deal with areas such as Space and Computer graphics as well as Game mechanics. His work in Generator addresses subjects such as Level design, which are connected to disciplines such as Evolutionary computation.

Between 2019 and 2021, his most popular works were:

  • Deep Learning for Video Game Playing (70 citations)
  • PCGRL: Procedural Content Generation via Reinforcement Learning (17 citations)
  • Increasing generality in machine learning through procedural content generation (15 citations)

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

  • Artificial intelligence
  • Machine learning
  • Programming language

Julian Togelius mainly focuses on Artificial intelligence, Content generation, Theoretical computer science, Reinforcement learning and Range. His Artificial intelligence research incorporates elements of Domain, Machine learning and Quality. His work in the fields of Machine learning, such as Overfitting, intersects with other areas such as Generality.

His studies in Theoretical computer science integrate themes in fields like Game mechanics, Translation and Dimension. Julian Togelius has included themes like Level design, Representation and Rotation in his Reinforcement learning study. The concepts of his Deep learning study are interwoven with issues in Game design, Multimedia, Artificial neural network and Unsupervised learning.

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.

Top 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)

713 Citations

Procedural Content Generation in Games

Noor Shaker;Julian Togelius;Mark J. Nelson.
(2016)

513 Citations

Experience-Driven Procedural Content Generation

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

487 Citations

Towards automatic personalised content creation for racing games

J. Togelius;R. De Nardi;S.M. Lucas.
computational intelligence and games (2007)

341 Citations

Artificial Intelligence and Games

Georgios N. Yannakakis;Julian Togelius.
(2018)

305 Citations

An experiment in automatic game design

J. Togelius;J. Schmidhuber.
computational intelligence and games (2008)

276 Citations

Modeling Player Experience for Content Creation

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

272 Citations

Towards automatic personalized content generation for platform games

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

243 Citations

The 2014 General Video Game Playing Competition

Diego Perez-Liebana;Spyridon Samothrakis;Julian Togelius;Tom Schaul.
IEEE Transactions on Computational Intelligence and AI in Games (2016)

218 Citations

Modeling player experience in Super Mario Bros

Chris Pedersen;Julian Togelius;Georgios N. Yannakakis.
computational intelligence and games (2009)

217 Citations

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

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