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for each agent i in population do.
In addition, agent i requests extra resources and agent j shares its resources with agent i.
An agent i holds a self-appreciation (kappa _{i i }).
For any agent i such that (v_iin (c^*_1,f, c^*_2,f)), agent i has double-peaked preferences over enforcement expenditure c.
That is, agent i with a large (L_C) comments only on articles posted by reciprocal agents who commented on past articles posted by agent i.
Algorithms Algorithm 4 Depeering by agent i using CBA and Algorithm 5 Peering by agent i using CBA give the procedures for depeering and peering respectively using CBA.
Intuitively, experience trust of agent (i) on agent (j) is the trustworthiness about (j) that agent (i) collects from all transactions between (i) and (j) in the past.
When agent i is caught (with probability p(c)), he pays a fine (f(h_i)).
An agent i holds a peer-appreciation (kappa _{ij}) of peer j.
Assume that r i denotes the state variable of agent i.
Agent i senses the state ({s^{i}_{t}}=s in mathcal {S}).
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Since I tried Ludwig back in 2017, I have been constantly using it in both editing and translation. Ever since, I suggest it to my translators at ProSciEditing.

Justyna Jupowicz-Kozak
CEO of Professional Science Editing for Scientists @ prosciediting.com