Abstract
In this work, we study an extension to evolutionary game models with the possibility to model the change and influence of the environment fluctuations for the fitness of the players. Using spatial games, those changes can be taken into account as an additional lattice dimension. In classical spatial evolutionary games (SEGT) each position on the lattice is represented by a single player or single phenotype (strategy). The local payoff for this player arises from the interactions with the neighbouring cells. With the newer approach each cell represents heterogeneous subpopulation, so can be considered as mixed or multidimensional spatial games (MSEG). This allows performing the game on a multidimensional lattice where an additional dimension is representing the evolution of resources.
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References
Bach, L., Bentzen, S., Alsner, J., Christiansen, F.: An evolutionary-game model of tumour-cell interactions: possible relevance to gene therapy. Eur. J. Cancer 37(16), 2116–2120 (2001). https://doi.org/10.1016/S0959-8049(01)00246-5
Bach, L.A., Sumpter, D.J.T., Alsner, J., Loeschcke, V.: Spatial evolutionary games of interaction among generic cancer cells. J. Theor. Med. 5(1), 47–58 (2003). https://doi.org/10.1080/10273660310001630443
Basanta, D., Gatenby, R.A., Anderson, A.R.A.: Exploiting evolution to treat drug resistance: combination therapy and the double bind. Mol. Pharm. 9(4), 914–921 (2012). https://doi.org/10.1021/mp200458e
Basanta, D., Hatzikirou, H., Deutsch, A.: Studying the emergence of invasiveness in tumours using game theory. Eur. Phy. J. B 63, 393–397 (2008). https://doi.org/10.1140/epjb/e2008-00249-y
Basanta, D., Scott, J.G., Fishman, M.N., Ayala, G., Hayward, S.W., Anderson, A.R.A.: Investigating prostate cancer tumour-stroma interactions: clinical and biological insights from an evolutionary game. Br. J. Cancer 106(1), 174–181 (2012). https://doi.org/10.1038/bjc.2011.517
Hofbauer, J., Schuster, P., Sigmund, K.: A note on evolutionary stable strategies and game dynamics. J. Theor. Biol. 81(3), 609–612 (1979). https://doi.org/10.1016/0022-5193(79)90058-4
Krześlak, M., Borys, D., Świerniak, A.: Angiogenic switch - mixed spatial evolutionary game approach. Intell. Inf. Database Syst. 9621, 420–429 (2016). https://doi.org/10.1007/978-3-662-49381-6_40
Krześlak, M., Świerniak, A.: Spatial evolutionary games and radiation induced bystander effect. Arch. Control Sci. 21(2), 135–151 (2011). https://doi.org/10.2478/v10170-010-0036-1
Krześlak, M., Świerniak, A.: Multidimensional extended spatial evolutionary games. Comput. Biol. Med. 69, 315–327 (2016). https://doi.org/10.1016/j.compbiomed.2015.08.003
Sigmund, K., Nowak, M.A.: Evolutionary game theory. Curr. Biol. 9(14), R503–R505 (1999). https://doi.org/10.1016/S0960-9822(99)80321-2
Smith, J.M.: Evolution and the Theory of Games. Cambridge University Press, Cambridge (1982). https://doi.org/10.1017/CBO9780511806292
Smith, J.M., Price, G.R.: The logic of animal conflict. Nature 246, 15–18 (1973). https://doi.org/10.1038/246015a0
Świerniak, A., Krześlak, M.: Application of evolutionary games to modeling carcinogenesis. Math. Biosci. Eng. MBE 10(3), 873–911 (2013). https://doi.org/10.3934/mbe.2013.10.873
Świerniak, A., Krześlak, M.: Cancer heterogeneity and multilayer spatial evolutionary games. Biol. Direct 11(1), 53 (2016). https://doi.org/10.1186/s13062-016-0156-z
Świerniak, A., Krześlak, M., Student, S., Rzeszowska-Wolny, J.: Development of a population of cancer cells: observation and modeling by a mixed spatial evolutionary games approach. J. Theor. Biol. 405, 94–103 (2016). https://doi.org/10.1016/j.jtbi.2016.05.027
Tomlinson, I., Bodmer, W.: Modelling the consequences of interactions between tumour cells. Br. J. Cancer 75(2), 157–160 (1997). https://doi.org/10.1038/bjc.1997.26
Acknowledgement
This work was supported by the Polish National Science Centre Grant no. DEC-2016/21/B/ST7/02241 (AS), the Institute of Automatic Control, Silesian University of Technology under Grant No. BK-204/RAU1/2017 (MK) and the National Centre for Research and Development Grant no. STRATEGMED2/ 267398/4/NCBR/2015 (MILESTONE – Molecular diagnostics and imaging in individualized therapy for breast, thyroid and prostate cancer) (DB). Calculations were performed on the Ziemowit computer cluster in the Laboratory of Bioinformatics and Computational Biology, created in the EU Innovative Economy Programme POIG.02.01.00-00-166/08 and expanded in the POIG.02.03.01-00-040/13 project.
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Swierniak, A., Krzeslak, M., Borys, D. (2019). Games with Resources and Their Use in Modeling Effects of Anticancer Treatment. In: Pietka, E., Badura, P., Kawa, J., Wieclawek, W. (eds) Information Technology in Biomedicine. ITIB 2018. Advances in Intelligent Systems and Computing, vol 762. Springer, Cham. https://doi.org/10.1007/978-3-319-91211-0_26
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