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The ﬁrst one involves only players with pure strategies. That is, each agent always plays the cooperate or the defect action. In the second scenario, we also consider a third type of agent that follows a mixed strategy. A mixed strategy is an assignment of a probability to each pure strategy (see details below). The action taken by a mixed strategy agent i depends on the weights of the links wij it has established with each of its opponents j ∈ g for the current game g. The average link weight for player i in game g is then deﬁned as: w i (g) = 1 |g| wij j∈g A mixed strategy i plays cooperatively in game g with probability: Pi (g) = wi (g)α + β w i (g)α + β + 1 With probability 1 − Pi (g), it plays defectively.
In contrast, an agent equipped with a mixed strategy plays a particular action based on a function of the reliability of other agents in its group in a given game. Thus, individual agents are able to adjust both these links and the action they play based on interactions with other agents. Detailed simulation experiments show that our model is able to promote higher levels of cooperation as compared with panmictic populations. An analysis of the social interactions between cooperative agents reveals high average clustering and associated single-to-broad-scale heterogeneity for relatively small values of N .
It is necessary to note that in the random neighbourhood structures, the neighbouring agents are being changed in every generation. (a) N = 4 (b) N = 5 Fig. 1. Fixed neighbourhood structures (a) N = 4 (b) N = 5 Fig. 2. 2 Strategy Representation There are various ways to represent the agent’s game-playing strategies. We have decided to adopt the representation developed by Yao and Darwen  as it is exponentially much shorter and easier to implement than the others. Under this representation, a history of l rounds for an agent can be represented as the combination of the following: l bits to represent the agent’s l previous actions.