In the case of anchoring, a common explanation is that the comparison value is used as a starting point for the subsequent judgment and adjusted until an "acceptable" answer is reached (Epley & Gilovich, 2006 Jacowitz & Kahneman, 1995 Lichtenstein & Slovic, 1971 Simmons et al., 2010 Tversky & Kahneman, 1974). We take this as suggestive that people deal with the inherent complexity of concept inference partly through use of local adaptive search in a latent compositional theory space. A particularly local variant of this adaptive account captures participants’ hypothesis revisions better than a range of alternative explanations. To explain this pattern, we develop a family of process accounts that combine program induction ideas with local (MCMC-like) adaptation mechanisms. We find an order effect whereby revised guesses are anchored to idiosyncratic elements of the earlier guess. In each case, we focus on the relationship between participants’ initial and revised guesses about the hidden rule concept. They then collect additional evidence themselves (Experiment 1) or observe evidence gathered by someone else (Experiment 2) before revising their own generalizations and guesses. Participants learn by performing mini-experiments before making generalizations and explicit guesses about a hidden rule. To explore this, we study human judgments in a challenging task that involves actively gathering evidence about a symbolic rule governing the behavior of a simulated environment. We investigate the idea that human concept inference utilizes local adaptive search within a compositional mental theory space. Resource-rational analysis to provide formal theories that can unify a wide range ofĮmpirical results and reconcile the impressive capacities of the human mind with its Towards provided versus self-generated anchors. This model provided a unifying explanation for tenĪnchoring phenomena including the differential effect of accuracy motivation on the bias Our analysis led to a rational process model that can be interpreted in terms ofĪnchoring-and-adjustment. Mathematical theory of bounded rationality to the problem of numerical estimation. What reasoning under uncertainty would look like if people made rational use of theirįinite time and limited cognitive resources.
We investigate whether rational theories can meet thisĬhallenge by taking into account the mind’s bounded cognitive resources. Cognitive biases, such as the anchoring bias, pose a serious challenge to rationalĪccounts of human cognition.
0 kommentar(er)
