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Fig 1.

Memory length m required for each of currently known friendly-rivalry strategies in the n-person PG game [18, 19, 21].

The dashed blue line depicts a theoretical lower bound m = n for friendly rivalry [19], and the strategy proposed in this work, called CAPRI-n, has m = 2n − 1.

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Fig 1 Expand

Fig 2.

Schematic diagram of the transition between states of CAPRI-n.

The five rules of the strategy can be identified with the player’s internal states [26], each of which is represented as a node in this diagram. An exception is state I, which corresponds to two nodes to clarify the following point: When t* ≥ tm, the state may have outgoing connections to A and P. When t* < tm, on the other hand, the only possible next state is R. The player has to choose c at a blue node and d at a red node. We have omitted error-caused transitions for the sake of simplicity.

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Fig 2 Expand

Fig 3.

Distribution of long-term payoffs when a CAPRI-n player meets co-players whose pμν’s are randomly sampled from the unit interval.

Darker shades toward blue indicate higher frequency of occurrence. The multiplication factors for n = 2, 3, and 4 are 1.5, 2, and 3, respectively, and the solid lines indicate the region of feasible payoffs. In each case, the filled circle means the long-term payoffs when CAPRI-n is adopted by all the players, whereas the cross shows those of TFT players as a reference point. In each panel, we have drawn a dotted line along the diagonal as a simple check for defensibility. For n = 3 or 4, the parallelogram surrounding the blue area indicates the set of feasible payoffs when the focal player is AllD, which indicates that the behavior of CAPRI-n is similar to AllD against most of the memory-one players.

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Fig 3 Expand

Fig 4.

Abundance of strategies for n = 2 as the benefit-to-cost ratio b and the population size N vary.

The default values were b = 3 and N = 30 unless otherwise specified. The strength of selection and the error probability were set to be σ = 1 and ϵ = 10−4, respectively. (A) Simulation result with 16 memory-one deterministic strategies, classified into three categories, i.e., efficient, defensible, and the other strategies. (B) Effect of CAPRI-2 when it was added to the available set of strategies.

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Fig 4 Expand

Fig 5.

Abundance of strategies for n = 3 as the benefit-to-cost ratio b and the population size N vary.

The default values were b = 3 and N = 30 unless otherwise specified. The strength of selection and the error probability were set to be σ = 1 and ϵ = 10−4, respectively. (A) Simulation result with 64 memory-one deterministic strategies, classified into three categories, i.e., efficient, defensible, and the other strategies. (B) Effect of CAPRI-3 when it was added to the available set of strategies.

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Fig 5 Expand

Fig 6.

Normalized distribution of fixation probabilities of mutants, which were randomly sampled from the set of deterministic strategies with the same memory length as CAPRI-n’s.

When we simulated the two-person game with taking CAPRI-2 as the resident strategy, 109 mutants were sampled. In case of the three-person game in which CAPRI-3 was the resident strategy, the number of sampled mutants was 5 × 106. In either case, no mutant had higher fixation probability than 1/N (the vertical dashed line). On the other hand, when the resident was randomly drawn from the same strategy set, mutants frequently achieved fixation with probability higher than 1/N. For each random sample of the resident strategy, 102 mutants were tested, and this process was repeated 107 and 105 times when n = 2 and 3, respectively. Throughout this calculation, we used N = 10 as the population size, ϵ = 10−4 as the error probability, σ = 1 as the selection strength, and b = 2 as the benefit of cooperation.

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Fig 6 Expand