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A Reputation Game Simulation: Emergent Social Phenomena from Information Theory

<p>Here, the data underlying the article &quot;A Reputation Game Simulation: Emergent Social Phenomena from Information Theory&quot; (<a href="https://doi.org/10.1002/andp.202100277">https://doi.org/10.1002/andp.202100277</a>) is&nbsp;provided.<br> <br> The data is structured&nbsp;according to the figures it has&nbsp;been used for. There are</p> <ul> <li>example simulations with basic communication strategies in the folder&nbsp;&quot;single_simulations_3_agents&quot; (Figures 4,5,8,D1)</li> <li>statistical simulations with 3 agents and special communication strategies in the folder&nbsp;&quot;statistical_simulations_3_agents&quot; (Figures 9-13, the upper panel of figure 15, figures&nbsp;16-18,&nbsp;D2 and&nbsp;the left panels of figure D3)</li> <li>statistical simulations with 4&nbsp;agents and special communication strategies in the folder&nbsp;&quot;statistical_simulations_4_agents&quot; (Figure 14, the middle panel of figure 15,&nbsp;the middle panels of figure D3 and&nbsp;the upper panels of figures D4, D5)</li> <li>statistical simulations with 5&nbsp;agents and special communication strategies in the folder&nbsp;&quot;statistical_simulations_5_agents&quot; (The lower panel of figure 15, the right panels of figure D3 and the lower panels of figures D4,D5)</li> <li>propaganda&nbsp;simulations&nbsp;in&nbsp;the&nbsp;folder&nbsp;&quot;propaganda_simulations&quot;&nbsp;(Figure&nbsp;7)</li> </ul> <p><br> Each simulation is represented by a .json file in which all events that&nbsp;happened during the simulation are collected. Generally, there are&nbsp;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&nbsp;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:</p> <ul> <li>parameters <ul> <li>decpeting:&nbsp;whether&nbsp;or&nbsp;not&nbsp;agents&nbsp;in&nbsp;generally&nbsp;make&nbsp;dishonest&nbsp;statements</li> <li>listening: whether or not agents in listen to their communication partners</li> <li>disturbing: whether or not agents are&nbsp;particularly risk-taking when making dishonest statements</li> <li>x_est:&nbsp;intrinsic&nbsp;honesties&nbsp;of&nbsp;the&nbsp;agents</li> <li>RSeed:&nbsp;the&nbsp;used&nbsp;random&nbsp;seed</li> <li>NA:&nbsp;number&nbsp;of&nbsp;agents</li> <li>NR:&nbsp;number&nbsp;of&nbsp;rounds</li> </ul> </li> <li>communication <ul> <li>a:&nbsp;speaker</li> <li>b:&nbsp;receiver</li> <li>c:&nbsp;topic</li> <li>J:&nbsp;transmitted&nbsp;message&nbsp;in&nbsp;the&nbsp;form&nbsp;of</li> </ul> </li> <li>self_update <ul> <li>id:&nbsp;number&nbsp;of&nbsp;agent&nbsp;who&nbsp;is&nbsp;updating&nbsp;knowledge&nbsp;about&nbsp;itself</li> <li>Nl, Nt: number of dishonest/honest statements the agent has observed from itself so far</li> <li>I_&lt;id&gt;: knowledge that the agents has about itself after the update in the form of</li> </ul> </li> <li>update <ul> <li>id:&nbsp;number&nbsp;of&nbsp;agent&nbsp;who&nbsp;is&nbsp;updating&nbsp;its&nbsp;knowledge</li> <li>I_&lt;id1&gt;: knowledge that the updating agent&nbsp;has about agent &lt;id1&gt;&nbsp;in the form of</li> <li>Jothers_&lt;id1&gt;_&lt;id2&gt;:&nbsp;last statement that the updating agent heared&nbsp;agent &lt;id1&gt; make about agent &lt;id2&gt;</li> <li>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</li> <li>Cothers_&lt;id1&gt;_&lt;id2&gt;: what the updating agent believes&nbsp;after the update that agent &lt;id1&gt; wants it to think&nbsp;about agent &lt;id2&gt;</li> <li>new_friends/enemies: id of the agent, the updating agent after the update considers&nbsp;a friend/enemy</li> <li>new_K: normalized surprise the updating agent experienced in the last communication (used to calculate kappa)</li> <li>kappa: median of the last ten normalized surprises the updating agent experienced</li> </ul> </li> <li>final_status <ul> <li>id/name:&nbsp;number&nbsp;if&nbsp;the&nbsp;described&nbsp;agent</li> <li>x:&nbsp;the&nbsp;agent&#39;s&nbsp;honesty</li> <li>I:&nbsp;the&nbsp;agent&#39;s&nbsp;knowledge&nbsp;about&nbsp;all&nbsp;others</li> <li>Nc/Nt/Nl: total number of conversations/honest statements/dishonest statements the agent has made</li> <li>K:&nbsp;the&nbsp;last&nbsp;10&nbsp;normalized&nbsp;surprises&nbsp;the&nbsp;agent&nbsp;experienced</li> <li>kappa:&nbsp;the&nbsp;median&nbsp;of&nbsp;K</li> <li>friends/enemies:&nbsp;list&nbsp;of&nbsp;the&nbsp;agent&#39;s&nbsp;friends/enemies</li> <li>Jothers/Iothers/Cothers: same as above, now as full array, i.e. the combined&nbsp;information about all others</li> <li>openess/mind/decepting/strategic/egocentric/deceptive/flattering/aggressive/shameless/disturbing: the agent&#39;s character traits</li> </ul> </li> </ul>

ShareScore

44/100

Overall dataset sharing score

Score breakdown

These five areas show where the dataset supports — or may limit — practical reuse.

Stewardship
8
Harmonization
4
Access
16
Reuse readiness
8
Engagement
8

Topics