Search Environments, Representation, and Encoding

This chapter explores the benefits of restructuring search spaces and internal representations so as to make search more efficient. It begins by providing a formal definition of search, and proposes a method for shifting search between low- and high-dimensionality problem spaces. Consideration is given to how learning shapes the representations that help people search efficiently as well as on constraints that people face. Some constraints are considered biases necessary to make sense out of the world; others (e.g., working memory) are taken as both “limiters” to be overcome and “permitters” that make learning in a finite amount of time possible at all. Further constraints on search are tied to the physical structure of the world. The chapter concludes with a discussion of social search, where communication can promote exploration and exploitation in an environment that often consists of other agents searching for similar solutions.