Human Decision Making and Information Sampling
Humans make surprisingly good decisions in everyday life; in fact, several researchers compare human decision making to rational inductive approaches like Bayesian analysis. However, unlike these rational approaches, humans are able to achieve optimality with limited information availability and manipulation capacity. This broad research area focuses on how humans make effective everyday decisions despite informational constraints and how they search for information to be included in decision samples. Our recent paper explored influence of recency biases and proposed that informational sampling limits stem from limitations in working memory capacity.