[robocup-worldwide] CfP: Special issue on Team AI in Games (IEEE Trans. on Games)

[Tomoharu NAKASHIMA]

CfP: IEEE Transactions on Games: Special Issue on Team AI in Games

http://transactions.games/Call%20for%20Papers.si.Team.AI.Final.pdf
http://transactions.games/

Editors: Maxim Mozgovoy (University of Aizu), Mike Preuss (Leiden
University), Tomoharu Nakashima (Osaka Prefecture University), and
Rafael Bidarra (Delft University of Technology).

Deadline for submissions: Friday, December 20, 2019

Recent years were marked with significant achievements of game
Artificial Intelligence (AI) systems. Computer-controlled players
excel in a wide range of environments, from traditional board games
like chess and Go to fast arcade environments like Super Mario Bros.
and one-vs-one fighting. One of the topical issues of today’s research
efforts aims at intelligent team behavior, relevant for a wide variety
of games, including real-time strategy games, team sports, multiplayer
online battle arena, and even tabletop games like Hanabi. The notion
of team behavior is very rich, ranging from the ability to exhibit a
clear and consistent strategy of an AI-controlled team to the
capability of “melting into” a group of human-controlled teammates and
supporting their coordinated actions. Consequently, design goals of an
AI system can be driven by a variety of considerations, including
efficiency, creativity, believability, synergism and contribution of
the AI to the overall entertainment value of the game. There is also
an imminent connection to artificial general intelligence (AGI)
because distributed AIs have to be quite adaptive to new situations,
including being confronted with other AIs that switch their behavior.
The purpose of this special issue of IEEE Transactions of Games is to
further explore these and related topics, both presenting the current
state of the art in team game AI systems, and offering a prime venue
for publishing new research results in this field. Primary topics of
interest include:
Development of efficient team strategies in various game genres.
Genre-specific AI design problems.
Approaches to team AI benchmarking.
Learning by observation methods for team AI development.
Evaluation principles of team behavior algorithms.
Emergent team behavior.
Design goals of team AI.
Believability and entertainment value of AI-controlled teams.
Teams of AI agents as opponents and teammates.
Authors should follow conventional Transactions on Games guidelines
for their submissions, but clearly identify that their papers are
aimed for this special issue. Three paper types will be considered for
publication: letters (up to 4 pages), full papers (up to 10 pages),
and survey papers (up to 15 pages). More information is available at
the journal homepage:

http://transactions.games/