When overconfident agents slow down collective learning
AbstractThis paper presents a model of influence where agents' beliefs are based on an objective reality, such as the properties of an environment. The perception of the objective reality is not direct: all agents know is that the more correct a belief, the more successful the actions that are deduced from this belief. (A pair of agents can influence each other when )Agents can influence eachother by pair when they perform a joint action. They are not only defined by individual beliefs, but also idyosynchratic confidence in their belief - this means that they are not all willing to (engage in action with) act with agents with a different belief and to be influenced by them. We show here that the distribution of confidence in the group has a huge impact on the speed and quality of collective learning and in particular that a small number of overconfident agents can prevent the whole group frow learning properly.
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Bibliographic InfoPaper provided by HAL in its series Université Paris1 Panthéon-Sorbonne (Post-Print and Working Papers) with number hal-00623966.
Date of creation: Jan 2012
Date of revision:
Publication status: Published, SIMULATION, 2012, 88, 1, 33-49
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agent-based computational economics; belief dissemination; bounded-confidence; simulation agents; social influence;
This paper has been announced in the following NEP Reports:
- NEP-ALL-2011-10-01 (All new papers)
- NEP-GTH-2011-10-01 (Game Theory)
- NEP-MIC-2011-10-01 (Microeconomics)
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