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
- Shallow decision-making analysis in General Video Game Playing
- Q-DeckRec: a Fast Deck Recommendation System for Collectible Card Games
- Inferring Design Constraints From Game Ruleset Analysis
- Intelligent Middle-Level Game Control
- Human-Like Playtesting with Deep Learning
- A Critical Analysis of Punishment in Public Goods Games
- Monte-Carlo Tree Search for Implementation of Dynamic Difficulty Adjustment Fighting Game AIs Having Believable Behaviors
- Monte-Carlo Tree Search Implementation of Fighting Game AIs Having Personas
- General Win Prediction from Agent Experience
- Building Evaluation Functions for Chess and Shogi with Uniformity Regularization Networks
- Regular Language Inference for Learning Rules of Simplified Boardgames
- Strategic Features and Terrain Generation for Balanced Heroes of Might and Magic III Maps
- Monte-Carlo Methods for the Game Kingdomino
- Evolving number sentence puzzles.
- Toward General Mathematical Game Playing
- Predicting skill learning outcomes in a large, longitudinal MOBA dataset
- An eye gaze model for controlling the display of social status in believable virtual humans
- Evolutionary Multi-objective Optimization of Real-Time Strategy Micro
- Monster Carlo: an MCTS-based Framework for Machine Playtesting Unity Games
- Deep RTS: A Game Environment for Deep Reinforcement Learning in Real-Time Strategy Games
- New And Surprising Ways to be Mean: Adversarial NPCs with Coupled Empowerment Minimisation
- Accelerating Empowerment Computation with UCT Tree Search
- Real-time Multi-agent heuristic search in videogame pathfinding
- Bayesian Opponent Exploitation in Imperfect-Information Games
- Geometry and Generation of a new Graph Planarity Game
- Ensemble Decision Making in Real-time Video Games
- Integrated Balancing of an RTS Game: Case Study and Toolbox Refinement
- Applying Commitment to Churn and Remaining Players Lifetime Prediction
- Neuroevolution of real-time strategy game micro
- Tabular Reinforcement Learning in Real-Time Strategy Games via Options
- Generating Novice Heuristics for Post-Flop Poker
- Scale-free Evolutionary Level Generation
- Hendrik Baier and Peter I. Cowling. Evolutionary MCTS for Multi-Action Adversarial Games
- 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
- Using a Surrogate Model of Gameplay for Automated Level Design
- Learning to Play General Video-Games via an Object Embedding Network
- Automated Curriculum Learning by Rewarding Temporally Rare Events
- Learning Map-Independent Evaluation Functions for Real-Time Strategy Games
- Jorge del Val, Imitation Learning with Concurrent Actions in 3D Games
- Deep reinforcement learning in the General Video Game AI framework
SS2: Intelligent Games for Learning
- Promotion of Learning Motivation through Individualization of Learner-Game Interaction
- A Virtual Agent Toolkit for Applied Game Developers
- The Influence of Feedback Choice on University Students’ Revision Choices and Performance in a Digital Assessment Game
- Plot from the Stars: educational game development for teaching basic mathematical functions
SS3: Integrating IoT Technologies with Serious Games
- Delivering Educational Scenarios using Internet of Things Data
- 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
Demos
- Baek In-Chang and Kim Kyung-Joong. Web-based Interface for Data Labeling in StarCraft