Restricted Intervals in Preference Dynamics: Theory and Application in an Agent-Based System
Authored by Steven D Silver, Marko Raseta
Date Published: 2015
DOI: 10.1109/tsmc.2014.2364556
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Abstract
Agent-based models have long been used to generate states of variables
at individual and aggregate levels. More recently, robotic and computer
agents are being given forms in which internal dispositions such as
cognitive reasoning, emotions, and preferences are represented. We note
limitations in most common representations of preferences in these
applications and propose conditions for dynamic forms of the variable. A
consequence of the dynamics we propose is that preferences exhibit
continuous variation in restricted intervals while maintaining
characteristic differences between entities and over time. After giving
a form to preferences in a situated application to a consumption system, analytical and computational methods are used to establish that dynamics
in the system have properties we describe. We then derive dependencies
of the restricted intervals in which preferences typically vary.
Estimation of these intervals is exemplified in data on the U.S.
economy. The system is then embodied in a network form in which cycle
and randomness from environments and their interactions are represented.
A demonstration of stochastic resonance in the networked system supports
the imputed dynamics. The network model is also used to indicate network
dependencies of the bounds of the interval in which preferences vary.
Finally, the relevance of the dynamics that are proposed in preferences
to other internal dispositions that include emotion in agent-based
models is discussed.
Tags
behavior
Opinion formation
noise
Decision-Making
Small-world networks
Model
growth
emotion
representation
Stochastic resonance