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

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-31
Author(s):  
George Butler ◽  
Gabriella Pigozzi ◽  
Juliette Rouchier
Keyword(s):  
Decision Making ◽  
Group Decision ◽  
Opinion Dynamics ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Agent Based Model ◽  
Social Modeling ◽  
Agent Based ◽  
Collective Decisions ◽  
Collective Deliberation

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.

Collective decision making, leadership, and collective intelligence: Tests with agent-based simulations and a Field study

2016 ◽  
Vol 27 (2) ◽  
pp. 218-241 ◽  
Author(s):  
Kristie A. McHugh ◽  
Francis J. Yammarino ◽  
Shelley D. Dionne ◽  
Andra Serban ◽  
Hiroki Sayama ◽  
...  
Keyword(s):  
Decision Making ◽  
Field Study ◽  
Collective Intelligence ◽  
Collective Decision ◽  
Intelligence Tests ◽  
Collective Decision Making ◽  
Agent Based ◽  
Agent Based Simulations

scholarly journals Closed-mindedness and insulation in groupthink: their effects and the devil’s advocacy as a preventive measure

2020 ◽  
Author(s):  
Muqtafi Akhmad ◽  
Shuang Chang ◽  
Hiroshi Deguchi
Keyword(s):  
Decision Making ◽  
Group Decision Making ◽  
Group Decision ◽  
Preventive Measure ◽  
Agent Based Model ◽  
Agent Based ◽  
Prevention Measure ◽  
Simulation Results

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.

scholarly journals Majority-rule opinion dynamics with differential latency: a mechanism for self-organized collective decision-making

2011 ◽  
Vol 5 (3-4) ◽  
pp. 305-327 ◽  
Author(s):  
Marco A. Montes de Oca ◽  
Eliseo Ferrante ◽  
Alexander Scheidler ◽  
Carlo Pinciroli ◽  
Mauro Birattari ◽  
...  
Keyword(s):  
Decision Making ◽  
Majority Rule ◽  
Opinion Dynamics ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Self Organized

scholarly journals Diversity and Social Network Structure in Collective Decision Making: Evolutionary Perspectives with Agent-Based Simulations

Complexity ◽  
2019 ◽  
Vol 2019 ◽  
pp. 1-16
Author(s):  
Shelley D. Dionne ◽  
Hiroki Sayama ◽  
Francis J. Yammarino
Keyword(s):  
Decision Making ◽  
Social Network ◽  
Network Structure ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Theoretic Approach ◽  
Agent Based ◽  
Social Network Structure ◽  
Agent Based Simulations ◽  
Simulation Results

Collective, especially group-based, managerial decision making is crucial in organizations. Using an evolutionary theoretic approach to collective decision making, agent-based simulations were conducted to investigate how human collective decision making would be affected by the agents’ diversity in problem understanding and/or behavior in discussion, as well as by their social network structure. Simulation results indicated that groups with consistent problem understanding tended to produce higher utility values of ideas and displayed better decision convergence, but only if there was no group-level bias in collective problem understanding. Simulation results also indicated the importance of balance between selection-oriented (i.e., exploitative) and variation-oriented (i.e., explorative) behaviors in discussion to achieve quality final decisions. Expanding the group size and introducing nontrivial social network structure generally improved the quality of ideas at the cost of decision convergence. Simulations with different social network topologies revealed collective decision making on small-world networks with high local clustering tended to achieve highest decision quality more often than on random or scale-free networks. Implications of this evolutionary theory and simulation approach for future managerial research on collective, group, and multilevel decision making are discussed.

The Elements of Collective Decision Making

2012 ◽  
pp. 1-31
Keyword(s):  
Artificial Intelligence ◽  
Decision Making ◽  
Group Decision Making ◽  
Real World ◽  
Group Decision ◽  
Collaborative Work ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Decision Science ◽  
Computer Supported Collaborative Work

In this chapter, the concept of a reasoning community is introduced. The overarching motivation is to understand reasoning within groups in real world settings so that technologies can be designed to better support the process. Four phases of the process of reasoning by a community are discerned: engagement of participants, individual reasoning, group coalescing, and, ultimately, group decision making. A reasoning community is contrasted with communities of practice and juxtaposed against concepts in related endeavours including computer supported collaborative work, decision science, and artificial intelligence.

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