Special Sessions

This is the final list of special sessions which will be included at CIG 2012.

Prospective authors are invited to contribute their papers to Special Session on Computational Creativity in Games. All papers have to be submitted electronically following the same process and formatting instructions as for regular papers, but choosing the correspondent special session trrack. See the submission section for more details.
All the accepted papers will be published in the proceedings of the conference.

Please contact the respective organizers or the special sessions chair if you have any question about them.

Computational Creativity in Games

Computational Intelligence (CI) techniques, including evolutionary computing, particle swarm optimization, ant colony optimization, differential evolution, neural networks, trajectory-based optimization methods, machine learning, constraint programming methods, and also (multi-)agent systems, data mining, influence mapping, ...,etc, have shown to be effective for search and optimization problems and have gained several promising results and becomes an important tool in Computational Creativity, such as in music, visual art, literature, architecture, and industrial design.
It is also well known (and globally accepted) that game programming requires a high level of creativity in a number of areas such as music composition, 2D/3D modelling, game narrative, game level/maps creation, player modelling, game AI, emergent behavior generation, and procedural content generation in general among others. In this context, computational intelligence techniques can play an important role in Game Creativity.
The aim of this special session is to reflect the most recent advances of Computational Creativity in Games, with the goal to enhance autonomous creative systems as well as human creativity in any area of the development of (video)games. This session will allow researchers to share experiences and present their new ways for taking advantage of CI techniques in Games Creativity.

Topics of interest include, but are not limited to, CI technologies applied to games in the following aspects:

Creativity in generation of music, visual art, architecture and design
Creativity in algorithmic design
Creativity in optimization
Creativity in development of hardware and software for games
Creativity in evaluation methodologies
Creativity in assistance of human creativity
Creativity in computational aesthetics
Creativity in emotion/emotional response
Creativity in human-machine creativity
Creativity in emergent behaviour
Creativity in 2D/3D modelling
Creativity in social games
Creativity in any genre of games including multiplayer games
Creativity in the automatic content generation for games (i.e., procedural content generation, track generation in racing games, map/level creation, dynamic terrain...)
Creativity in board games
Creativity in Opponent modelling
Creativity in Player modelling/prediction
Creativity in representation issues
Creativity in mate behavior in games (e.g., squad coordination in first person shooter games or in real time strategy games).
Creativity in motion planning
Creativity in combat reasoning

organizers: Carlos Cotta and Antonio J. Fernández Leiva

Monte Carlo Tree Search for Games

Monte Carlo Tree Search (MCTS) is a novel tree search algorithm that has led to recent breakthroughs in computer Go and other games. MCTS, unlike classical tree search algorithms, is any-time and does not necessarily require a state value function. These attributes make MCTS a promising candidate for games in which traditional tree search algorithms tend to fail. MCTS has been applied successfully to a wide variety of games, including puzzles, board games, card games and real-time video games, and has produced world champion AI players for a number of difficult games. More recently, MCTS has also been proposed as a method for automated level and game design.
The aim of this special session is to highlight these advances and to bring together high quality publications concerning the study, analysis and application of MCTS with respect to games.

Topics of interest include, but are not limited to:

MCTS for intelligent move planning
MCTS for opponent modelling
Learning in MCTS
Hybrid MCTS algorithms
MCTS for real-time (video) games
MCTS for continuous domains
MCTS for open-ended (infinite) domains
MCTS for nondeterministic / hidden information games
MCTS for social (multiplayer / euro / bidding / gambling) games
MCTS for solitaire puzzle design and solving
MCTS for game, content and level design
Enhancements and variations of MCTS

organizers: Philipp Rohlfshagen, Edward Powley and Cameron Browne

Computational Intelligence in Racing Games

Modern racing games provide vivid representations of the game environment and very realistic physics engines that accurately model the dynamics of racing cars. At the same time, they also need a very sophisticated and believable AI to meet the increasingly high expectations of players.
Computational intelligence offers a range of interesting new ideas and techniques for racing game developers. So far, both published academic research, the entrants of the recurring simulated car racing competitions, and some notable applications in high-end commercial games have shown that computational intelligence techniques can successfully be used in the racing games domain.
The aim of this special session is to bring together leading researchers in this field and gather the best new research, the most innovative ideas, and the future directions within this research area.

Topics of interest include, but are not limited to, the following:

On-line Learning in Racing Games
Player/Opponent Modeling in Racing Games
CI-based Gameplay for Racing Games
Procedural Game Content Generation in Racing Games
Player Satisfaction and Experience Modelling and Optimization in Racing Games
Novel CI Platforms & Benchmarks Based on Racing Games
CI Applications in Racing Games

organizers: Pier Luca Lanzi, Luigi Cardamone and Daniele Loiacono

Game Data Mining

Since the first computer game, the behavior of the players has been registered, and responses to these behaviors calculated in real-time. In recent years extracting logs of player behavior, game telemetry, has enabled game researchers and game developers to adopt behavioral analysis at hitherto unprecedented levels of resolution. In addition, contemporary commercial computer games provide an ideal environment for the study of human behavior. Being closed worlds of considerable complexity, games allow for investigating behavior patterns, decision making, and preference modeling.
Advances in these areas serve both to improve our understanding of players and learning in games, and improving game design and game play. Game data mining has a high potential as an enabler of future business, but requires for recording and storage of large amounts of telemetry data as well as efficient methods for the processing and analysis of large scale data sets.

Topics of interest for this special session include, but are not limited to, the following:

In-game telemetry data collection
Practical applications of game mining
Efficient representation and visualization of in-game data
Algorithms for (large scale) game mining
User modeling based on behavioral telemetry data
Player evaluation and playability testing
Computational intelligence for behavior pattern analysis
Empirical studies based on telemetry data
Future directions for in-game data mining

organizers: Christian Thurau, Anders Drachen, Alessandro Canossa, Christian Bauckhage and Kristian Kersting

Version 2.5 - September, 2012

Important Dates