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There are two types of reciprocity: (W^m_i = {jin W_i | iin W_j}) is the set of mutual reciprocal agents of i, and (W^o_i = {jin W_i | inot in W_j}) is the set of one-sided reciprocal agents of i.
Thus, while agents received more rewards from non-reciprocal agents by behaving like free riders, they commented on the articles posted by reciprocal agents.
Table 3 lists the relationship between the number of reciprocal agents and the network type.
Fig. 14 Relationship between memory term and number of reciprocal agents.
Thus, hub agents receive sufficient comments, have some reciprocal agents, and, thereby, continue posting articles.
Agent i has a memory for reciprocal agents (W_i) (({subset} {A_i})), which is the set of reciprocal agents that are defined as neighbor agents that posted comments on i's articles in the most recent (T_{rm{W}} ({0})) rounds.
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However, when i has a longer memory, i would continue to consider j to be a reciprocal agent.
Then, if j did not comment on i's articles in a few rounds, i would still assume that j is a reciprocal agent.
However, this instability can be avoided by making two assumptions: high degree of fun, i.e. articles are read with high probability, and different attitudes to reciprocal and non-reciprocal agents.
However, this phenomenon raises in complete graphs under the additional conditions that (1) agents seldom miss the posted articles and (2) they do not comment on articles posted by non-reciprocal agents.
However, if we manipulate the RRG so that users hardly miss any articles posted by their neighbors but at the same time hardly comment on articles posted by non-reciprocal agents, cooperation emerges.
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Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com