The full proceedings of IEEE CIG 2018 is available here.

CIG18 Accepted Full Papers

Papers are ordered by submission id. Any paper accepted for oral presentation or poster will be published as a full 8-page paper in the proceedings.

Main Track

  • Ivan Bravi, Diego Perez, Simon Lucas and Jialin Liu. Shallow decision-making analysis in General Video Game Playing
  • Zhengxing Chen, Chris Amato, Magy Seif El-Nasr, Truong Nguyen, Seth Cooper and Yizhou Sun. Q-DeckRec: a Fast Deck Recommendation System for Collectible Card Games
  • Michael Cook, Simon Colton and Azalea Raad. Inferring Design Constraints From Game Ruleset Analysis
  • Amin Babadi, Kourosh Naderi and Perttu Hämäläinen. Intelligent Middle-Level Game Control
  • Stefan Gudmundsson, Philipp Eisen, Erik Poromaa, Alex Nodet, Sami Purmonen, Richard Meurling, Bartlomiej Kozakowski and Lele Cao. Human-Like Playtesting with Deep Learning
  • Garry Greenwood, Hussein Abbass and Eleni Petraki. A Critical Analysis of Punishment in Public Goods Games
  • Makoto Ishihara, Suguru Ito, Ryota Ishii, Tomohiro Harada and Ruck Thawonmas. Monte-Carlo Tree Search for Implementation of Dynamic Difficulty Adjustment Fighting Game AIs Having Believable Behaviors
  • Ryota Ishii, Suguru Ito, Makoto Ishihara, Tomohiro Harada and Ruck Thawonmas. Monte-Carlo Tree Search Implementation of Fighting Game AIs Having Personas
  • Raluca Gaina, Simon Lucas and Diego Perez Liebana. General Win Prediction from Agent Experience
  • Shanchuan Wan and Tomoyuki Kaneko. Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks
  • Jakub Kowalski and Andrzej Kisielewicz. Regular Language Inference for Learning Rules of Simplified Boardgames
  • Jakub Kowalski, Radoslaw Miernik, Piotr Pytlik, Maciej Pawlikowski, Krzysztof Piecuch and Jakub Sekowski. Strategic Features and Terrain Generation for Balanced Heroes of Might and Magic III Maps
  • Magnus Gedda, Mikael Zayenz Lagerkvist and Martin Butler. Monte-Carlo Methods for the Game Kingdomino
  • Daniel Ashlock and Courtney Kolthof. Evolving number sentence puzzles.
  • Daniel Ashlock, Eun-Youn Kim and Diego Pérez-Liébana. Toward General Mathematical Game Playing
  • Myat Aung, Valerio Bonometti, Anders Drachen, Peter Cowling, Athanasios Kokkinakis and Alex Wade. Predicting skill learning outcomes in a large, longitudinal MOBA dataset
  • Michael Nixon, Steve Dipaola and Ulysses Bernardet. An eye gaze model for controlling the display of social status in believable virtual humans
  • Rahul Dubey, Joseph Ghantous, Sushil Louis and Siming Liu. Evolutionary Multi-objective Optimization of Real-Time Strategy Micro
  • Oleksandra Keehl and Adam Smith. Monster Carlo: an MCTS-based Framework for Machine Playtesting Unity Games
  • Per-Arne Andersen, Morten Goodwin and Ole-Christoffer Granmo. Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games
  • Christian Guckelsberger, Christoph Salge and Julian Togelius. New And Surprising Ways to be Mean: Adversarial NPCs with Coupled Empowerment Minimisation
  • Christoph Salge, Christian Guckelsberger, Rodrigo Canaan and Tobias Mahlmann. Accelerating Empowerment Computation with UCT Tree Search
  • Devon Sigurdson, Vadim Bulitko, William Yeoh, Sven Koenig and Carlos Hernandez. Real-time Multi-agent heuristic search in videogame pathfinding
  • Sam Ganzfried and Qinyung Sun. Bayesian Opponent Exploitation in Imperfect-Information Games
  • Rutger Kraaijer, Marc Van Kreveld, Wouter Meulemans and Andre van Renssen. Geometry and Generation of a new Graph Planarity Game
  • Philip Rodgers, John Levine and Damien Anderson. Ensemble Decision Making in Real-time Video Games
  • Mike Preuss, Thomas Pfeiffer, Vanessa Volz and Nicolas Pflanzl. Integrated Balancing of an RTS Game: Case Study and Toolbox Refinement
  • Luiz Bernardo Martins Kummer, Júlio César Nievola and Emerson Paraiso. Applying Commitment to Churn and Remaining Players Lifetime Prediction
  • Aavaas Gajurel, Sushil J. Louis, Daniel J. Mendez and Siming Liu. Neuroevolution of real-time strategy game micro
  • Anderson R. Tavares and Luiz Chaimowicz. Tabular Reinforcement Learning in Real-Time Strategy Games via Options
  • Fernando De Mesentier Silva, Julian Togelius, Frank Lantz and Andy Nealen. Generating Novice Heuristics for Post-Flop Poker
  • André Siqueira Ruela and Karina Valdivia Delgado. Scale-free Evolutionary Level Generation
  • Hendrik Baier and Peter I. Cowling. Evolutionary MCTS for Multi-Action Adversarial Games
  • Frank Glavin and Michael Madden. Skilled Experience Catalogue: A Skill-Balancing Mechanism for Non-Player Characters using Reinforcement Learning
  • Mohammed Salem, Antonio Mora and Juan J. Merelo. The evolutionary race: improving the process of evaluating car controllers in racing simulators

SS1: Deep Learning in Games

  • Daniel Karavolos, Antonios Liapis and Georgios N. Yannakakis. Using a Surrogate Model of Gameplay for Automated Level Design
  • William Woof and Ke Chen. Learning to Play General Video-Games via an Object Embedding Network
  • Niels Justesen and Sebastian Risi. Automated Curriculum Learning by Rewarding Temporally Rare Events
  • Zuozhi Yang and Santiago Ontañón. Learning Map-Independent Evaluation Functions for Real-Time Strategy Games
  • Jack Harmer, Linus Gisslen, Jorge del Val, Henrik Holst, Joakim Bergdahl, Tom Olsson, Kristoffer Sjöö and Magnus Nordin. Imitation Learning with Concurrent Actions in 3D Games
  • Ruben Rodriguez Torrado, Philip Bontrager, Julian Togelius, Jialin Liu and Diego Perez Liebana. Deep reinforcement learning in the General Video Game AI framework

SS2: Intelligent Games for Learning

  • Sandra Kaczmarek and Sintija Petroviča. Promotion of Learning Motivation through Individualization of Learner-Game Interaction
  • Samuel Mascarenhas, Rui Prada, João Dias, Pedro A. Santos, Kam Star, Ben Hirsh, Ellis Spice and Rob Kommeren. A Virtual Agent Toolkit for Applied Game Developers
  • Maria Cutumisu. The Influence of Feedback Choice on University Students’ Revision Choices and Performance in a Digital Assessment Game
  • Gabriel Toschi de Oliveira, Hugo Henriques Pereira, Claudio Fabiano Motta Toledo, Seiji Isotani and Geiser Chaclo Challco. Plot from the Stars: educational game development for teaching basic mathematical functions

SS3: Integrating IoT Technologies with Serious Games

  • Chrysanthi Tziortzioti, Irene Mavrommati and Ioannis Chatzigiannakis. Delivering Educational Scenarios using Internet of Things Data
  • Evaggelos Spyrou, Nicholas Vretos, Andrew Pomazanskyi, Stylianos Asteriadis and Helen Leligou. Exploiting IoT Technologies for Personalized Learning
  • Pavlos Kosmides, Konstantinos Demestichas, Evgenia Adamopoulou, Nikos Koutsouris, Yannis Oikonomidis and Vanessa De Luca. InLife: Combining Real Life with Serious Games using IoT

Short Papers

  • Vadim Bulitko and Kacy Doucet. Anxious Learning in Real-time Heuristic Search
  • Kun Shao, Dongbin Zhao, Nannan Li and Yuanheng Zhu. Learning Battles in ViZDoom via Deep Reinforcement Learning
  • Chiara F. Sironi and Mark H. M. Winands. Analysis of Self-adaptive Monte Carlo Tree Search in General Video Game Playing
  • Chrysoula Varia, Georgios Tsatiris, Kostas Karpouzis and Stefanos Kollias. A refined 3D dataset for the analysis of player actions in exertion games
  • Paul Bertens, Anna Guitart, Pei Pei Chen and Africa Perianez. A Machine-Learning Item Recommendation System for Video Games
  • Simon Lucas. Game AI Research with Fast Planet Wars Variants
  • Emil Gensby, Anders Harbøll Christiansen and Bo Friis Nielsen. Multi-Parametrised Matchmaking: A Framework
  • Benjamin Bell. Learning to Play Doom with Separate Action Outputs
  • Adam Streck and Thomas Wolbers. Using Discrete Time Markov Chains for Control of Idle Character Animation

Competition Papers

  • Rodrigo de Moura Canaan, Haotian Shen, Ruben Torrado, Julian Togelius, Andy Nealen and Stefan Menzel. Evolving Agents for the Hanabi 2018 CIG Competition
  • Pavan Kantharaju, Santiago Ontanon and Christopher Geib. μCCG, a CCG-based Game-Playing Agent for μRTS
  • Maciej Świechowski, Tomasz Tajmajer and Andrzej Janusz. Improving Hearthstone AI by Combining MCTS and Supervised Learning Algorithms
  • Alexander Dockhorn and Daan Apeldoorn. Forward Model Approximation for General Video Game Learning
  • Martin L.M. Rooijackers and Mark H. M. Winands. Wall Building in the Game of StarCraft with Terrain Considerations
  • Yoshina Takano, Wenwen Ouyang, Suguru Ito, Tomohiro Harada and Ruck Thawonmas. Applying Hybrid Reward Architecture to a Fighting Game AI
  • Bryan Weber. Standard Economic Models in Nonstandard Settings- StarCraft:Brood Wars

Vision Papers

  • Cameron Browne. Modern Techniques for Ancient Games
  • Cristina Guerrero-Romero, Simon Lucas and Diego Perez-Liebana. Using a Team of General AI Algorithms to Assist Game Design and Testing
  • Rodrigo de Moura Canaan, Stefan Menzel, Julian Togelius and Andy Nealen. Towards Game-based Metrics for Computational Co-creativity
  • Vanessa Volz, Kevin Majchrzak and Mike Preuss. A Bottom-Up Approach to Explanations for (Game) AI
  • Jichen Zhu, Antonios Liapis, Sebastian Risi, Rafael Bidarra and Michael Youngblood. Explainable AI for Designers: A Human-Centered Perspective on Mixed-Initiative Co-Creation


  • Baek In-Chang and Kim Kyung-Joong. Web-based Interface for Data Labeling in StarCraft