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In the model this competition is represented by the game. 2) The game tests the strategies of the individuals under the rules of the game. These rules produce different payoffs – in units of fitness (the production rate of offspring). The contesting individuals meet in pairwise contests with others, normally in a highly mixed distribution of ...
2780 14686 Ensembl ENSG00000134183 ENSMUSG00000009108 UniProt P19087 P50149 RefSeq (mRNA) NM_005272 NM_001377295 NM_001379232 NM_008141 RefSeq (protein) NP_005263 NP_001364224 NP_001366161 NP_032167 Location (UCSC) Chr 1: 109.6 – 109.62 Mb Chr 3: 108 – 108.01 Mb PubMed search Wikidata View/Edit Human View/Edit Mouse Guanine nucleotide-binding protein G(t) subunit alpha-2 is a protein that ...
In mathematics, the replicator equation is a deterministic monotone non-linear and non-innovative game dynamic used in evolutionary game theory. [1] The replicator equation differs from other equations used to model replication, such as the quasispecies equation, in that it allows the fitness function to incorporate the distribution of the population types rather than setting the fitness of a ...
An infinitely-repeated game without discounting is often called a "supergame". The folk theorem in this case is very simple and contains no pre-conditions: every individually rational and feasible payoff profile in the basic game is a Nash equilibrium payoff profile in the repeated game.
An extensive form representation of a signaling game. In game theory, a signaling game is a type of a dynamic Bayesian game. [1] The essence of a signaling game is that one player takes action, the signal, to convey information to another player. Sending the signal is more costly if the information is false.
Graphically drawing a high dimensional hypercube on the 2-dimensional plane remains a difficult task, and one crude locator of a rule in the hypercube is the number of bit-1 in the 8-bit string for elementary rules (or 32-bit string for the next-nearest-neighbor rules).
To break the shell of the mollusk, the crows fly and drop the whelks on rocks. Reto Zach constructed an optimality model to predict the optimal height at which crows drop the whelks. [17] The benefit in this model is the success rate of cracking the whelk's shell, while the primary cost is the energy spent flying.
Structure of a gene regulatory network Control process of a gene regulatory network. A gene (or genetic) regulatory network (GRN) is a collection of molecular regulators that interact with each other and with other substances in the cell to govern the gene expression levels of mRNA and proteins which, in turn, determine the function of the cell.