Johan Hagelbäck

发表

The Effect of Emotions and Social Behavior on Performance in a Collaborative Serious Game Between Humans and Autonomous Robots

Veronica Sundstedt, Johan Hagelbäck, Petar Jercic, 2018, Int. J. Soc. Robotics.

Bachelor Degree Project Hierarchical Temporal Memory Software Agent

Johan Hagelbäck, Jakob Heyder, 2018 .

Bachelor Thesis Project Generation, evaluation, and optimisation of procedural 2D tile-based maps in turn-based tactical video games

Johan Hagelbäck, 2016 .

The 29th Annual Workshop of the Swedish Artificial Intelligence Society (SAIS) 2–3 June 2016, Malmö, Sweden Editor

Christos Dimitrakakis, P. Davidsson, F. Heintz, 2016 .

Bachelor Degree Project

Johan Hagelbäck, 2022 .

Using machine learning to classify news

Johan Hagelbäck, Jesper Holmström, Eleonor Lagerkrants, 2016 .

Using multi-agent potential fields in real-time strategy games

Stefan J. Johansson, Johan Hagelbäck, S. Johansson, 2008, AAMAS.

Locating transmembrane domains in protein sequences

Johan Hagelbäck, Kenny Svensson, 2003 .

Bachelor Degree Project Automated classification of bibliographic data using SVM and Naive Bayes

Johan Hagelbäck, 2018 .

Classifying receipts or invoices from images based on text extraction

Johan Hagelbäck, Narges Khakpour, 2016 .

Applying automated testing in an existing client-server game A pursuit for fault localization in Quake 3

Johan Hagelbäck, T. Ohlsson, 2016 .

Thesis Project Performance evaluation of routing protocols for Wireless Mesh Networks

Johan Hagelbäck, S. Marinis, 2016 .

Multi-Agent Potential Field Based Architectures for Real-Time Strategy Game Bots

Johan Hagelbäck, Johan Hagelbäck, 2012 .

A Multiagent Potential Field-Based Bot for Real-Time Strategy Games

Stefan J. Johansson, Johan Hagelbäck, S. Johansson, 2009, Int. J. Comput. Games Technol..

A Multi-Agent PotentiAl Field bAsed APProAch For reAl-tiMe strAtegy gAMe bots

Johan Hagelbäck, Johan Hagelbäck, 2009 .

Dealing with fog of war in a Real Time Strategy game environment

Stefan J. Johansson, Johan Hagelbäck, S. Johansson, 2008, 2008 IEEE Symposium On Computational Intelligence and Games.

The Rise of Potential Fields in Real Time Strategy Bots

Stefan J. Johansson, Johan Hagelbäck, S. Johansson, 2008, AIIDE.

THE PERFORMANCE OF SOME MACHINE LEARNING APPROACHES IN HUMAN MOVEMENT ASSESSMENT

Welf Löwe, Johan Hagelbäck, Alisa Lincke, 2019, Proceedings of the 11th International Conference on e-Health 2019.

Variants of Dynamic Time Warping and their Performance in Human Movement Assessment

Johan Hagelbäck, Welf Löwe, Pavlo Liapota, 2019 .

On the Agreement of Commodity 3D Cameras

Johan Hagelbäck, Welf Löwe, Alisa Lincke, 2019, ICIP 2019.

Controllable procedural map generation via multiobjective evolution

Julian Togelius, Nicola Beume, Mike Preuss, 2013, Genetic Programming and Evolvable Machines.

Psychophysiological Interaction and Empathic Cognition for Human-Robot Cooperative Work (PsyIntEC)

Johan Svensson, Stefan J. Johansson, Johan Hagelbäck, 2014, Technology Transfer Experiments from the ECHORD Project.

An affective serious game for collaboration between humans and robots

Johan Hagelbäck, Petar Jerčić, Craig A. Lindley, 2019, Entertain. Comput..

Multiobjective exploration of the StarCraft map space

Julian Togelius, Nicola Beume, Mike Preuss, 2010, Proceedings of the 2010 IEEE Conference on Computational Intelligence and Games.

Measuring player experience on runtime dynamic difficulty scaling in an RTS game

Stefan J. Johansson, Johan Hagelbäck, S. Johansson, 2009, 2009 IEEE Symposium on Computational Intelligence and Games.

Evaluating Classifiers for Emotion Recognition Using EEG

Johan Hagelbäck, Olle Hilborn, Petar Jercic, 2013, HCI.

Automatic Classification Using DDC on the Swedish Union Catalogue

Koraljka Golub, Anders Ardö, Johan Hagelbäck, 2018, NKOS@TPDL.

Using dated training sets for classifying recent news articles with Naive Bayes and Support Vector Machines-An experiment comparing the accuracy of classifications using test sets from 2005 and 2017

Johan Hagelbäck, 2022 .

Hybrid Pathfinding in StarCraft

Johan Hagelbäck, Johan Hagelbäck, 2016, IEEE Transactions on Computational Intelligence and AI in Games.

Evaluation of Classifiers for Emotion Detection While Performing Physical and Visual Tasks: Tower of Hanoi and IAPS

Johan Hagelbäck, Craig A. Lindley, Syed Muhammad Zeeshan Iqbal, 2018, IntelliSys.

Potential-field based navigation in StarCraft

Johan Hagelbäck, Johan Hagelbäck, 2012, 2012 IEEE Conference on Computational Intelligence and Games (CIG).