Tag Archive: Agents

Oct 28

Rationality: A Social-Epistemology Perspective

Authors: Sylvia Wenmackers, Danny E. P. Vanpoucke, and Igor Douven
Journal: Front. Psychol. 5, 581 (2014)
doi: 10.3389/fpsyg.2014.00581
IF(2014): 2.560
export: bibtex
pdf: <Front.Psychol.> (open Access)

Abstract

Both in philosophy and in psychology, human rationality has traditionally been studied from an ‘individualistic’ perspective. Recently, social epistemologists have drawn attention to the fact that epistemic interactions among agents also give rise to important questions concerning rationality. In previous work, we have used a formal model to assess the risk that a particular type of social-epistemic interactions lead agents with initially consistent belief states into inconsistent belief states. Here, we continue this work by investigating the dynamics to which these interactions may give rise in the population as a whole.

Oct 28

Probability of inconsistencies in theory revision,
A multi-agent model for updating logically interconnected beliefs under bounded confidence

Authors: Sylvia Wenmackers, Danny E. P. Vanpoucke, and Igor Douven
Journal: Eur. Phys. J. B 85, 44 (2012)
doi: 10.1140/epjb/e2011-20617-8
IF(2012): 1.282
export: bibtex
pdf: <Eur.Phys.J.B>

Abstract

We present a model for studying communities of epistemically interacting agents who update their belief states by averaging (in a specified way) the belief states of other agents in the community. The agents in our model have a rich belief state, involving multiple independent issues which are interrelated in such a way that they form a theory of the world. Our main goal is to calculate the probability for an agent to end up in an inconsistent belief state due to updating (in the given way). To that end, an analytical expression is given and evaluated numerically, both exactly and using statistical sampling. It is shown that, under the assumptions of our model, an agent always has a probability of less than 2% of ending up in an inconsistent belief state. Moreover, this probability can be made arbitrarily small by increasing the number of independent issues the agents have to judge or by increasing the group size. A real-world situation to which this model applies is a group of experts participating in a Delphi-study.