scholarly journals Understanding the Mechanisms of Collective Decision Making in Ecological Restoration: An Agent-Based Model of Actors and Organizations

2013 ◽  
Vol 18 (2) ◽  
Author(s):  
Cristy Watkins ◽  
Dean Massey ◽  
Jeremy Brooks ◽  
Kristen Ross ◽  
Moira L. Zellner
Keyword(s):  
Decision Making ◽  
Ecological Restoration ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Agent Based Model ◽  
Agent Based

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 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.

MODELLING Collective Decision-Making: Insights Into COLLECTIVE anti-predator Behaviors From AN Agent-Based APPROACH

2021 ◽  
pp. 104530
Author(s):  
Julia Watzek ◽  
Mark E. Hauber ◽  
Katharine M. Jack ◽  
Julie R. Murrell ◽  
Stacey R. Tecot ◽  
...  
Keyword(s):  
Decision Making ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Agent Based

Usefulness of Agent-Based Simulation in Testing Collective Decision-Making Models

2014 ◽  
pp. 72-87 ◽  
Author(s):  
Pablo Lucas ◽  
Diane Payne
Keyword(s):  
Decision Making ◽  
Computer Simulations ◽  
Policy Decision ◽  
Collective Decision ◽  
Collective Decision Making ◽  
Agent Based ◽  
Peer Review Journal ◽  
Decision Making Models ◽  
Collective Negotiations ◽  
Other Regarding

Political scientists seek to build more realistic Collective Decision-Making Models (henceforth CDMM) which are implemented as computer simulations. The starting point for this present chapter is the observation that efficient progress in this field may be being hampered by the fact that the implementation of these models as computer simulations may vary considerably and the code for these computer simulations is not usually made available. CDMM are mathematically deterministic formulations (i.e. without probabilistic inputs or outputs) and are aimed at explaining the behaviour of individuals involved in dynamic, collective negotiations with any number of policy decision-related issues. These CDMM differ from each other regarding the particular bargaining strategies implemented and tested in each model for how the individuals reach a collective binding policy agreement. The CDMM computer simulations are used to analyse the data and generate predictions of a collective decision. While the formal mathematical treatment of the models and empirical findings of CDMM are usually presented and discussed through peer-review journal publications, access to these CDMM implementations as computer simulations are often unavailable online nor easily accessed offline and this tends to dissuade cross fertilisation and learning in the field.

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