Model Synthesis and Model-Oriented Programming A New Technology for High Performance Agent-Based Modeling

2018 ◽  
Author(s):  
Yury I. Brodsky
Keyword(s):  
High Performance ◽  
New Technology ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Model Synthesis

Large-Scale Social Simulation, Dealing with Complexity Challenges in High Performance Environments

2014 ◽  
pp. 106-123 ◽  
Author(s):  
C. Montañola-Sales ◽  
X. Rubio-Campillo ◽  
J. Casanovas-Garcia ◽  
J. M. Cela-Espín ◽  
A. Kaplan-Marcusán
Keyword(s):  
Information Technology ◽  
Computer Simulations ◽  
Real World ◽  
High Performance ◽  
Large Scale ◽  
Social Dynamics ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Important Amount ◽  
Distributed Implementation

Advances on information technology in the past decades have provided new tools to assist scientists in the study of social and natural phenomena. Agent-based modeling techniques have flourished recently, encouraging the introduction of computer simulations to examine behavioral patterns in complex human and biological systems. Real-world social dynamics are very complex, containing billions of interacting individuals and an important amount of data (both spatial and social). Dealing with large-scale agent-based models is not an easy task and encounters several challenges. The design of strategies to overcome these challenges represents an opportunity for high performance parallel and distributed implementation. This chapter examines the most relevant aspects to deal with large-scale agent-based simulations in social sciences and revises the developments to confront technological issues.

In Conclusion

2017 ◽  
Author(s):  
Michael Laver ◽  
Ernest Sergenti
Keyword(s):  
New Technology ◽  
Political Process ◽  
Computational Approach ◽  
Agent Based Modeling ◽  
Human Beings ◽  
Agent Based ◽  
Party Leaders ◽  
Response Strategies ◽  
Best Response ◽  
Rules Of Thumb

This concluding chapter summarizes key themes and presents some final thoughts. This book started with the twin premises that understanding multiparty competition is a core concern for everyone interested in representative democracy and that multiparty competition should be understood as an evolving dynamic system, not a stationary state. Given these premises, it investigated the dynamics of multiparty competition using computational agent-based modeling, a new technology that is ideally suited to providing systematic answers to the types of question we want to ask. This allows the modeling of decision making by party leaders, in what is clearly an analytically intractable setting, in terms of the informal rules of thumb that might be used by real human beings, rather than the formally provable best response strategies used by traditional formal theorists. Whether people use the dynamic model of multiparty competition or some better model of this vital but complex political process, there is no doubt that the computational approach deployed in this book offers vast potential to ask and answer interesting and important questions.

scholarly journals High-Performance Agent-Based Modeling Applied to Vocal Fold Inflammation and Repair

2018 ◽  
Vol 9 ◽  
Author(s):  
Nuttiiya Seekhao ◽  
Caroline Shung ◽  
Joseph JaJa ◽  
Luc Mongeau ◽  
Nicole Y. K. Li-Jessen
Keyword(s):  
Vocal Fold ◽  
High Performance ◽  
Agent Based Modeling ◽  
Agent Based

Party Competition

2017 ◽  
Author(s):  
Michael Laver ◽  
Ernest Sergenti
Keyword(s):  
Political Parties ◽  
New Technology ◽  
Agent Based Modeling ◽  
Party Competition ◽  
Computational Techniques ◽  
Comprehensive Treatment ◽  
Agent Based ◽  
Political Actors ◽  
Theoretical Approaches ◽  
Political Landscapes

Party competition for votes in free and fair elections involves complex interactions by multiple actors in political landscapes that are continuously evolving, yet classical theoretical approaches to the subject leave many important questions unanswered. This book offers the first comprehensive treatment of party competition using the computational techniques of agent-based modeling. This exciting new technology enables researchers to model competition between several different political parties for the support of voters with widely varying preferences on many different issues. The book models party competition as a true dynamic process in which political parties rise and fall, a process where different politicians attack the same political problem in very different ways, and where today's political actors, lacking perfect information about the potential consequences of their choices, must constantly adapt their behavior to yesterday's political outcomes. This book shows how agent-based modeling can be used to accurately reflect how political systems really work. It demonstrates that politicians who are satisfied with relatively modest vote shares often do better at winning votes than rivals who search ceaselessly for higher shares of the vote. It reveals that politicians who pay close attention to their personal preferences when setting party policy often have more success than opponents who focus solely on the preferences of voters, that some politicians have idiosyncratic “valence” advantages that enhance their electability—and much more.

Agent-Based Modeling and High Performance Computing

2016 ◽  
pp. 79-111 ◽  
Author(s):  
Maksudul Alam ◽  
Vida Abedi ◽  
Josep Bassaganya-Riera ◽  
Katherine Wendelsdorf ◽  
Keith Bisset ◽  
...  
Keyword(s):  
High Performance Computing ◽  
High Performance ◽  
Agent Based Modeling ◽  
Agent Based ◽  
Performance Computing

Care HPS: A high performance simulation tool for parallel and distributed agent-based modeling

2017 ◽  
Vol 68 ◽  
pp. 59-73 ◽  
Author(s):  
Francisco Borges ◽  
Albert Gutierrez-Milla ◽  
Emilio Luque ◽  
Remo Suppi
Keyword(s):  
High Performance ◽  
Agent Based Modeling ◽  
Simulation Tool ◽  
Performance Simulation ◽  
Agent Based
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