Paper Info
Title
Sociality, Sanctions, Damaging Behaviors: A Distributed Implementation of an Agent-Based Social Simulation Model.
Abstract
The explanatory and predictive power of social simulations is more and more connected with the development of models accounting for the complexity of real (inter-individual and intra-individual) social dynamics. From this perspective, a promising research path is complementing very simple models, more suitable to illuminate core dynamics of social phenomena, with increasingly more complex and empirically grounded simulations (big data-driven models, higher number of agents, more detailed and realistic description of cognitive and communication mechanisms underlying individual and group behaviors). The choice has two strictly intertwined effects: not only a different modeling approach, but also the need for more powerful tools. The paper presents a distributed implementation of an agent-based model exploring the interplay between damaging behaviors, sanctions and social mechanisms of learning and imitation, a topic investigated in many areas of social science from economics to legal science. Taking cue from a previous work based on a simple NetLogo simulation, the work shows how distributed solutions can help in developing more complex, wide and semantically rich models.
Year
DOI
Venue
2013
10.1007/978-3-642-54420-0_58
Lecture Notes in Computer Science
Keywords
Field
DocType
Agent-based simulation models,Parallel Computing,Distributed Systems,High Performance Computing,Socially Behaviours
Data science,Sanctions,Predictive power,Supercomputer,Computer science,Agent-based social simulation,Sociality,Social dynamics,Cognition,Distributed computing
Conference
Volume
ISSN
Citations 
8374
0302-9743
0
PageRank 
References 
Authors
0.34
6
6
Name
Order
Citations
PageRank
Michele Carillo181.94
Nicola Lettieri231.08
Domenico Parisi3745101.62
Francesco Raia4111.39
Flavio Serrapica581.94
Luca Vicidomini6144.27