The Game of Life, Decision and Communication


The game of life represents a spatial environment of cells that live and die according to fixed rules of nature. In the basic variant of the game a cell’s behavior can be described as reactive and deterministic since each cell’s transition from an actual state to a subsequent state is straight-forwardly defined by the rules. Furthermore, it can be shown that the alive cells’ spatial occupation share of the environment decreases quickly and levels out at a really small value (around 3%), virtually independent of the initial number of alive cells. In this study we will show that this occupation share can be strongly increased if alive cells become more active by making non-deterministic sacrificial decisions according to their individual positions. Furthermore, we applied signaling games in combination with reinforcement learning to show that results can be even more improved if cells learn to signal for navigating the behavior of neighbor cells. This result stresses the assumption that individual behavior and local communication supports the optimization of resourcing and constitute important steps in the evolution of creature and man.


Share and Cite:

Mühlenbernd, R. and Schulz, S. (2014) The Game of Life, Decision and Communication. Natural Science, 6, 1093-1102. doi: 10.4236/ns.2014.613097.

Conflicts of Interest

The authors declare no conflicts of interest.


[1] Gardner, M. (1970) Mathematical Games: The Fantastic Combinations of John Conway’s New Solitaire Game “Life”. Scientific American, 223, 120-123.
[2] Roth, A.E. and Erev, I. (1995) Learning in Extensive-Form Games: Experimental Data and Simple Dynamic Models in the Intermediate Term. Games and Economic Behaviour, 8, 164-212.
[3] Lewis, D. (1969) Convention. A Philosophical Study. Harvard University Press, Cambridge, MA.
[4] Skyrms, B. (2010) Signals: Evolution, Learning & Information. Oxford University Press, Cambridge, MA.

Copyright © 2023 by authors and Scientific Research Publishing Inc.

Creative Commons License

This work and the related PDF file are licensed under a Creative Commons Attribution 4.0 International License.