Applications
Multi-Scenario World II. Results PDF Print E-mail
EMIL Results Page

Figures

 

File
 TitleDescription
 figures.pdf     Document of figures.

 

Videos

 

File
Description
 run1_0sec.avi Run 1, 0 second
 run1_1450sec_infobox.avi Run 1, 1450 seconds with information boxes
 run1_3960sec.avi Run 1, 3960 seconds
 run1_6000sec.avi Run 1, 6000 seconds
 run1_7860sec.avi Run 1, 7860 seconds
 run2_0sec.avi Run 2, 0 second
 run2_3960sec.avi Run 2, 3960 seconds
 run2_8580sec_60msRL.avi Run 2, 8580 seconds, 60 ms RL

 

Textual Results

 

File
Description
 50k.txt   50.000 time step
 50k_0-33.txt  50.000 time step, 33% norm recognizer
 50k_0-66.txt  50.000 time step, 66% norm recognizer

 

 

Publications

  1.  Campenni, M., Andrighetto, G., Cecconi, F., Conte, R. (2008) Normal = Normative? The Role of Intelligent Agents in Norm Innovation. ESSA 2008.
 
Social Normative Compliance Description PDF Print E-mail

 

Model name:   Social Normative Compliance
 Model title:
  Social Vs Normative Compliance
 Replicated model?
  No
 Keywords:  Social Compliance, Normative Compliance, Normative Architecture, Normative Effects on Environment
 Model authors:
  Marco Campennì, Federico Cecconi, Giulia Andrighetto, Roasaria Conte
 Programming language?  NetLogo, Version: 4.0.4

 

The patches have to be coloured by agents. Each agent randomly moves in the world and when it meets another agent (this means that another agent falls in the radius of observation  of the first agent) they can interact. During the interaction social conformers interact imitating each others and norm recognizers interact recording in their architecture observed behaviors and received deontics (in this model we use a simplified version of the social input described above). At the beginning norm recognizers have in their normative board normative beliefs with randomly assigned salience. Runtime, norm recognizers can change the salience of their normative beliefs in accordance with observed behavior and received deontics (increasing the salience when the normative threshold is reached, namely the right number of i) observed behaviors and ii) received deontics are recorded; decreasing the salience, when the action corresponding to the normative belief is not very often used). In the case in which agents can also follow the colors' gradient, agents choose the direction searching the zones of the world where the color they most use in colouring the patches is the most used.


DOCUMENTATION

1. Purpose

The Model aims to show the environmental effects of the norm recognition module use; simple social compliance effects are compared with normative compliance ones

2. State variables and scales

Social Conformers act imitating other agents and trying to perturbate as less as possible the environment; Norm Recognizers act processing information received by other agents to perform the action that perturbs as less as possible the environment.

3. Process overview and scheduling

Agents randomly move in the environment and they have to color the patches they reach with one of three possible colors: red, black or gray (each color has a different rate of environmental perturbation: red and black rate > gray rate). Social Conformers act imitating other agents, Norm recognizers act and exchange messages with other agents they meet.
 
4. Design concepts

 

  4.1 Emergence

 More or less unifomity in the color of the patches that constitute the world.

 4.2 Adaptation


 4.3 Fitness


 4.4 Prediction


 4.5 Sensing

 Agents observe the state of the world (e.g. the color of the patch where they are) and Norm Recognizers can process received information by means of the three layer architecure they are equipped with.

 4.6 Interaction

 Agents randomly move in the world and they interact with other agents they meet.

 4.7 Stochasticity

 A stochastic approach to initialize the modals sent at the beginning of the simulation (when agents have no normative beliefs in their minds) is used.

 4.8 Collectives


 4.9 Observation


5. Initialization


6. Input


7. Submodels

 
Social Normative Compliance Results PDF Print E-mail

 

Figures

 

File
 TitleDescription
 50_uh.png  Snapshot
 50_wuh.png  Snapshot
 conf1_wuh.png  Snapshot
 conf2_uh.png  Snapshot
 model.png  Snapshot
 norm1_wuh.png  Snapshot
 norm2_uh.png  Snapshot

 

Videos

 

File
Description

 

Textual Results

 

File
Description
 result1 (.csv)
 Table: half and half and all normative
 result2 (.csv)
 Table: only conformers

 

 

Publications

 

 
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