In coevolution, the fitness of a solution is determined not (only) by
a fixed fitness function, but also by the other solution(s) being
evaluated. Thus, coevolution has the potential to overcome several
problems with static fitness functions, paving the way for more open-
ended evolution. However, several phenomena common to coevolutionary
algorithms are at present poorly understood, including cycling and
loss of gradient. Further understanding of such phenomena would
facilitate more widespread use of coevolutionary algorithms.
This special session seeks to bring together research that uses
coevolutionary algorithms to learn to play games, uses games to
investigate coevolution, or uses coevolution as a basis for game
design. Due to their adversarial nature, often involving interaction
of multiple agents, games are uniquely suited to be combined with
coevolution. We invite both theoretical and applied work in the
intersection of coevolution and games, including but not limited to
the following topics:
Competitive coevolution
Cooperative coevolution
Multiple populations in coevolution
Coevolution with diverse representations
Theory of coevolution
Preventing cycling and loss of gradient
Coevolution-based game design
Self-play and coevolutionary-like reinforcement learning
Relative versus absolute fitness metrics
About the organisers:
Julian Togelius is a researcher at the Dalle Molle Institute for
Artificial Intelligence (IDSIA) in Lugano, Switzerland. His research
interests include evolving game-playing agents, modelling player
behaviour, and evolving interesting game content, mainly using
evolutionary and coevolutionary techniques. He also co-organizes the
well-attended Simulated Car Racing Competitions for the IEEE CIG and
CEC conferences.
Philip Hingston is an associate professor of computer science at Edith
Cowan University in Perth. His research interests are in the theory
and application of artificial intelligence and computational
intelligence. He has a particular interest in evolutionary computation
as a tool for design, and in computer games. He is chair of the IEEE
CIS Task Force on co-evolution. More information can be found on his
home page at: http://www.scis.ecu.edu.au/Staff/staffinfo.aspx?staffid=phingsto.
Alan Blair is Chair of the IEEE CIS Task Force on Co-evolution and
Games. His research interests include robot navigation, image and
language processing as well as co-evolutionary learning for
Backgammon, Tron, IPD, simulated hockey and language games. His
homepage is at: http://www.cse.unsw.edu.au/~blair.
> In coevolution, the fitness of a solution is determined not (only) by
> a fixed fitness function, but also by the other solution(s) being
> evaluated. Thus, coevolution has the potential to overcome several
> problems with static fitness functions, paving the way for more open-
> ended evolution. However, several phenomena common to coevolutionary
> algorithms are at present poorly understood, including cycling and
> loss of gradient. Further understanding of such phenomena would
> facilitate more widespread use of coevolutionary algorithms.
> This special session seeks to bring together research that uses
> coevolutionary algorithms to learn to play games, uses games to
> investigate coevolution, or uses coevolution as a basis for game
> design. Due to their adversarial nature, often involving interaction
> of multiple agents, games are uniquely suited to be combined with
> coevolution. We invite both theoretical and applied work in the
> intersection of coevolution and games, including but not limited to
> the following topics:
> Competitive coevolution
> Cooperative coevolution
> Multiple populations in coevolution
> Coevolution with diverse representations
> Theory of coevolution
> Preventing cycling and loss of gradient
> Coevolution-based game design
> Self-play and coevolutionary-like reinforcement learning
> Relative versus absolute fitness metrics
> About the organisers:
> Julian Togelius is a researcher at the Dalle Molle Institute for
> Artificial Intelligence (IDSIA) in Lugano, Switzerland. His research
> interests include evolving game-playing agents, modelling player
> behaviour, and evolving interesting game content, mainly using
> evolutionary and coevolutionary techniques. He also co-organizes the
> well-attended Simulated Car Racing Competitions for the IEEE CIG and
> CEC conferences.
> Philip Hingston is an associate professor of computer science at Edith
> Cowan University in Perth. His research interests are in the theory
> and application of artificial intelligence and computational
> intelligence. He has a particular interest in evolutionary computation
> as a tool for design, and in computer games. He is chair of the IEEE
> CIS Task Force on co-evolution. More information can be found on his
> home page at:http://www.scis.ecu.edu.au/Staff/staffinfo.aspx?staffid=phingsto.
> Alan Blair is Chair of the IEEE CIS Task Force on Co-evolution and
> Games. His research interests include robot navigation, image and
> language processing as well as co-evolutionary learning for
> Backgammon, Tron, IPD, simulated hockey and language games. His
> homepage is at:http://www.cse.unsw.edu.au/~blair.
Last reminder - less that a week to go for CIG papers. Still time to
polish off that coevolution paper and submit to the Special Session on
Coevolution in Games. The weather in Perth is perfect for the beach in
December!
2008 IEEE Symposium on Computational Intelligence and Games (CIG'08)
Perth, Australia, 15-18 December 2008
http://www.csse.uwa.edu.au/cig08/
!!!!!!!!!!!!!! PAPER SUBMISSION CLOSES 15 AUGUST
2008 !!!!!!!!!!!!!!!
Featuring:
- three world-class plenary speakers: Jonathan Schaeffer from the
University of Alberta, Penny Sweetser from 2K Games, and Jason
Hutchens from Interzone Entertainment;
- special sessions in four emerging areas: Computational Intelligence
in Real Time Strategy Games, Player Satisfaction, Coevolution in
Games, and Player/Opponent Modeling;
- free introductory tutorials by Simon Lucas, Bobby Bryant, Georgios
Yannakakis and Julian Togelius; and
- a number of exciting competitions that showcase the application of
computational intelligence techniques in games.
Games have proven to be an ideal domain for the study of computational
intelligence as not only are they fun to play and interesting to
observe, but they provide competitive and dynamic environments that
model many real-world problems. This symposium, sponsored by the IEEE
Computational Intelligence Society with technical co-sponsorship from
the IEEE Consumer Electronics Society, aims to bring together leading
researchers and practitioners from both academia and industry to
discuss recent advances and explore future directions in this field.
> > In coevolution, the fitness of a solution is determined not (only) by
> > a fixed fitness function, but also by the other solution(s) being
> > evaluated. Thus, coevolution has the potential to overcome several
> > problems with static fitness functions, paving the way for more open-
> > ended evolution. However, several phenomena common to coevolutionary
> > algorithms are at present poorly understood, including cycling and
> > loss of gradient. Further understanding of such phenomena would
> > facilitate more widespread use of coevolutionary algorithms.
> > This special session seeks to bring together research that uses
> > coevolutionary algorithms to learn to play games, uses games to
> > investigate coevolution, or uses coevolution as a basis for game
> > design. Due to their adversarial nature, often involving interaction
> > of multiple agents, games are uniquely suited to be combined with
> > coevolution. We invite both theoretical and applied work in the
> > intersection of coevolution and games, including but not limited to
> > the following topics:
> > Competitive coevolution
> > Cooperative coevolution
> > Multiple populations in coevolution
> > Coevolution with diverse representations
> > Theory of coevolution
> > Preventing cycling and loss of gradient
> > Coevolution-based game design
> > Self-play and coevolutionary-like reinforcement learning
> > Relative versus absolute fitness metrics
> > About the organisers:
> > Julian Togelius is a researcher at the Dalle Molle Institute for
> > Artificial Intelligence (IDSIA) in Lugano, Switzerland. His research
> > interests include evolving game-playing agents, modelling player
> > behaviour, and evolving interesting game content, mainly using
> > evolutionary and coevolutionary techniques. He also co-organizes the
> > well-attended Simulated Car Racing Competitions for the IEEE CIG and
> > CEC conferences.
> > Philip Hingston is an associate professor of computer science at Edith
> > Cowan University in Perth. His research interests are in the theory
> > and application of artificial intelligence and computational
> > intelligence. He has a particular interest in evolutionary computation
> > as a tool for design, and in computer games. He is chair of the IEEE
> > CIS Task Force on co-evolution. More information can be found on his
> > home page at:http://www.scis.ecu.edu.au/Staff/staffinfo.aspx?staffid=phingsto.
> > Alan Blair is Chair of the IEEE CIS Task Force on Co-evolution and
> > Games. His research interests include robot navigation, image and
> > language processing as well as co-evolutionary learning for
> > Backgammon, Tron, IPD, simulated hockey and language games. His
> > homepage is at:http://www.cse.unsw.edu.au/~blair.- Hide quoted text -
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