Dynamics of decision making: from evidence to preference and belief At the core of the many debates throughout cognitive science concerning how decisions are made are the processes governing the time course of preference formation and decision. From perceptual choices, such as whether the signal on a radar screen indicates an enemy missile or a spot on a CT scan indicates a tumor, to cognitive value-based decisions, such as selecting an agreeable flatmate or deciding the guilt of a defendant, significant and everyday decisions are dynamic over time. Phenomena such as decoy effects, preference reversals and order effects are still puzzling researchers. For example, in a legal context, jurors receive discrete pieces of evidence in sequence, and must integrate these pieces together to reach a singular verdict. From a standard Bayesian viewpoint the order in which people receive the evidence should not influence their final decision, and yet order effects seem a robust empirical phenomena in many decision contexts. Current research on how decisions unfold, especially in a dynamic environment, is advancing our theoretical understanding of decision making. |
Contents
from evidence accumulation to preference and belief | 5 |
Linear deterministic accumulator models of simple choice | 8 |
Do the dynamics of prior information depend on task context? An analysis of optimal performance and an empirical test | 27 |
Can posterror dynamics explain sequential reaction time patterns? | 42 |
bounded diffusion vs the leaky competing accumulator model | 58 |
theoretical and empirical developments | 75 |
Evidence accumulator or decision threshold which cortical mechanism are we observing? | 94 |
EEG oscillations reveal neural correlates of evidence accumulation | 108 |
The influence of initial beliefs on judgments of probability | 145 |
The role of inertia in modeling decisions from experience with instancebased learning | 153 |
the influences of data serial order data consistency and elicitation timing | 165 |
an eyetracking analysis | 181 |
The attentional driftdiffusion model extends to simple purchasing decisions | 199 |
The 2Nary choice tree model for Nalternative preferential choice | 217 |
A quantum probability model of causal reasoning | 228 |
A canonical theory of dynamic decisionmaking | 241 |
The nature of beliefdirected exploratory choice in human decisionmaking | 121 |
Prediction and control in a dynamic environment | 133 |