scholarly journals Corrigendum to “Mixing Dyadic and Deliberative Opinion Dynamics in an Agent-Based Model of Group Decision-Making”

Complexity ◽  
2021 ◽  
Vol 2021 ◽  
pp. 1-1
Author(s):  
George Butler ◽  
Juliette Rouchier ◽  
Gabriella Pigozzi

Author(s):  
Muqtafi Akhmad ◽  
Shuang Chang ◽  
Hiroshi Deguchi

Abstract This paper’s purpose is to clarify groupthink phenomena and to assess the devil’s advocacy as a groupthink prevention measure. An agent-based model is presented to formalize group closed-mindedness and insulation in a group decision making setting. The model was validated by showing that groupthink results in the decision with low quality and the group’s inability to explore more alternatives. Besides that, the devil’s advocacy also formulated in the model. The simulation results of different conditions of the devil’s advocacy support Janis’ suggestion to utilize the devil’s advocacy to alleviate groupthink. It is also found that the utilization of devil’s advocacy depends on the group’s condition and the desired amount of conflict to produce the best decision.


2007 ◽  
Vol 362 (1485) ◽  
pp. 1699-1710 ◽  
Author(s):  
W.I Sellers ◽  
R.A Hill ◽  
B.S Logan

We present an agent-based model of the key activities of a troop of chacma baboons ( Papio hamadryas ursinus ) based on the data collected at De Hoop Nature Reserve in South Africa. We analyse the predictions of the model in terms of how well it is able to duplicate the observed activity patterns of the animals and the relationship between the parameters that control the agent's decision procedure and the model's predictions. At the current stage of model development, we are able to show that across a wide range of decision parameter values, the baboons are able to achieve their energetic and social time requirements. The simulation results also show that decisions concerning movement (group action selection) have the greatest influence on the outcomes. Those cases where the model's predictions fail to agree with the observed activity patterns have highlighted key elements that were missing from the field data, and that would need to be collected in subsequent fieldwork. Based on our experience, we believe group decision making is a fertile field for future research, and agent-based modelling offers considerable scope for understanding group action selection.


Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-31
Author(s):  
George Butler ◽  
Gabriella Pigozzi ◽  
Juliette Rouchier

In this article, we propose an agent-based model of opinion diffusion and voting where influence among individuals and deliberation in a group are mixed. The model is inspired from social modeling, as it describes an iterative process of collective decision-making that repeats a series of interindividual influences and collective deliberation steps, and studies the evolution of opinions and decisions in a group. It also aims at founding a comprehensive model to describe collective decision-making as a combination of two different paradigms: argumentation theory and ABM-influence models, which are not obvious to combine as a formal link between them is required. In our model, we find that deliberation, through the exchange of arguments, reduces the variance of opinions and the proportion of extremists in a population as long as not too much deliberation takes place in the decision processes. Additionally, if we define the correct collective decisions in the system in terms of the arguments that should be accepted, allowing for more deliberation favors convergence towards the correct decisions.


Author(s):  
Russell A. Hill ◽  
Brian S. Logan ◽  
William I. Sellers ◽  
Julian Zappala

Complexity ◽  
2010 ◽  
Vol 16 (3) ◽  
pp. 49-57 ◽  
Author(s):  
Hiroki Sayama ◽  
Dene L. Farrell ◽  
Shelley D. Dionne

2021 ◽  
Vol 11 (1) ◽  
Author(s):  
Allegra A. Beal Cohen ◽  
Rachata Muneepeerakul ◽  
Gregory Kiker

AbstractMany agent-based models (ABMs) try to explain large-scale phenomena by reducing them to behaviors at lower scales. At these scales in social systems are functional groups such as households, religious congregations, coops and local governments. The intra-group dynamics of functional groups often generate inefficient or unexpected behavior that cannot be predicted by modeling groups as basic units. We introduce a framework for modeling intra-group decision-making and its interaction with social norms, using the household as our focus. We select phenomena related to women’s empowerment in agriculture as examples influenced by both intra-household dynamics and gender norms. Our framework proves more capable of replicating these phenomena than two common types of ABMs. We conclude that it is not enough to build multi-scale models; explaining social behaviors entails modeling intra-scale dynamics.


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