Rocco Scolozzi

Department of Sociology and Social Research, University of Trento, 

-skopìa s.r.l. Anticipation Services®

www.skopia-anticipation.it

Uta Schirpke

Accademia Europea di Bolzano (EURAC),

Istituto per l’Ambiente Alpino

www.eurac.edu

Rocco Scolozzi

-skopìa Anticipation Services, innovative startup of Trento University 

www.skopia-anticipation.it

Uta Schirpke

Accademia Europea di Bolzano (EURAC),

Istituto per l’Ambiente Alpino

www.eurac.edu 

www.lifemgn-serviziecosistemici.eu

Rocco Scolozzi

-skopìa Anticipation Services, innovative startup of Trento University 

www.skopia-anticipation.it

Uta Schirpke

Accademia Europea di Bolzano (EURAC),

Istituto per l’Ambiente Alpino

www.eurac.edu 

www.lifemgn-serviziecosistemici.eu

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

Rocco Scolozzi

-skopìa Anticipation Services, innovative startup of Trento University 

www.skopia-anticipation.it

Uta Schirpke

Accademia Europea di Bolzano (EURAC),

Istituto per l’Ambiente Alpino

www.eurac.edu 

www.lifemgn-serviziecosistemici.eu

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.

An implementation of the classic Game of Life using agent based modeling.

• A live cell with less than two alive neighbors dies.
• A live cell with more than three alive neighbors dies.
• A dead cell with three neighbors becomes alive.