A tutorial on partially observable Markov decision processes

The partially observable Markov decision process (POMDP) model of environments was first explored in the engineering and operations research communities 40 years ago. More recently, the model has been embraced by researchers in artificial intelligence and machine learning, leading to a flurry of solution algorithms that can identify optimal or near-optimal behavior in many environments represented as POMDPs. The purpose of this article is to introduce the POMDP model to behavioral scientists who may wish to apply the framework to the problem of understanding normative behavior in experimental settings. The article includes concrete examples using a publicly-available POMDP solution package.     

Gender and Form of Cereal Box Characters: Different Medium, Same Disparity

We investigated the extent to which male characters outnumber female characters on cereal boxes, and the extent to which male and female characters are portrayed in gender stereotypical ways. Cereal boxes (N?=?217) from a large grocery store in the northeastern United States were examined. Characters on the front and back of the boxes were coded for gender, species (person, animal, object), age (child/adolescent, adult), and activity level (passive/sedentary, active). Male characters outnumbered female characters by more than 2 to 1. Female characters were more likely than male characters to be depicted as people and as children/adolescents, whereas male characters were more likely than female characters to be portrayed as animals and as adults. Suggestions for further research are discussed.     

The need for accuracy in historiography.

Historiographers must be especially accurate in their citations and references. An article by Wettersten contained numerous incorrect references and citations, and factual errors. Corrections are provided.