Information and Agreement in the Reputation Game Simulation
2022-12-01

Here, the data underlying the article "Information and Agreement in the Reputation Game Simulation" is provided.<br> <br> There are 100 simulations with different random seeds to ensure statistically meaningful results. Each simulation is represented by a .json file in which all events that happened during the simulation are collected. Generally, there are three types of events: communications, self-updates (information that the speaker gained about itself is processed) and updates (information that the receiver gained about the speaker and the topic is processed). Additionally, the first line specifies the parameters of each simulation, and the last few lines summarize the final status of the simulation. In the following all important abbreviations are explained: first line x_est: intrinsic honesties of the agents fr_affinities: intrinsic friendship affinity values of the agents shynesses: intrinsic shyness values of the agents perc_one_to_one: percentage of one-to-one conversations RSeed: the used random seed NA: number of agents NR: number of rounds mode: strategy used by the special agent communication a: speaker b_set: set of receivers. Can be either a single receiver or several c: topic J: transmitted message in the form of self_update id: number of agent who is updating knowledge about itself Nl, Nt: number of dishonest/honest statements the agent has observed from itself so far I_&lt;id&gt;: knowledge that the agents has about itself after the update in the form of Jothers_&lt;id1&gt;_&lt;id2&gt;: last statement that the updating agent heared agent &lt;id1&gt; make about agent &lt;id2&gt; update id: number of agent who is updating its knowledge I_&lt;id1&gt;: knowledge that the updating agent has about agent &lt;id1&gt; in the form of Jothers_&lt;id1&gt;_&lt;id2&gt;: last statement that the updating agent heared agent &lt;id1&gt; make about agent &lt;id2&gt; Iothers_&lt;id1&gt;_&lt;id2&gt;: what the updating agent believes that agent &lt;id1&gt; thinks about agent &lt;id2&gt; after the update Cothers_&lt;id1&gt;_&lt;id2&gt;: what the updating agent believes after the update that agent &lt;id1&gt; wants it to think about agent &lt;id2&gt; relationsc_&lt;id&gt;: number of conversations the updating agent has had with agent &lt;id&gt; relationsm_&lt;id&gt;: number of messages the updating agent received about agent &lt;id&gt; friendship+_to_&lt;id&gt;: the updating agent counts one friendly statement of agent &lt;id&gt;, i.e. the updating agent rates agent &lt;id&gt; now a little more as a friend friendship-_to_&lt;id&gt;: the updating agent counts one unfriendly statement of agent &lt;id&gt;, i.e. the updating agent rates agent &lt;id&gt; now a little more as an enemy new_K: normalized surprise the updating agent experienced in the last communication (used to calculate kappa) kappa: median of the last ten normalized surprises the updating agent experienced final_status id/name: number if the described agent x/fr_affinity/shyness: the agent's intrinsic personality traits I: the agent's knowledge about all others Nc/Nt/Nl: total number of conversations/honest statements/dishonest statements the agent has made relationsm/relationsc: number of messages (conversations) the agent heard about (had with) all others K: the last 10 normalized surprises the agent experienced kappa: the median of K friendships: the agent's friendship status with all others, given as parameters of a beta function Jothers/Iothers/Cothers: same as above, now as full array, i.e. the combined information about all others openess/mind/decepting/strategic/egocentric/deceptive/flattering/aggressive/shameless/disturbing: the agent's character traits