An Instance-based Model of the Effect of Previous Choices on the Control of Interactive Search

An Instance-based Model of the Effect of Previous Choices on the Control of Interactive Search Andrew Howes (HowesA@cardiff.ac.uk) School of Psychology, Cardiff University, Cardiff, CF10 3YG, Wales, UK Stephen J. Payne (PayneS@cardiff.ac.uk) School of Psychology, Cardiff University, Cardiff, CF10 3YG, Wales, UK Juliet Richardson School of Psychology, Cardiff University, Cardiff, CF10 3YG, Wales, UK Abstract How do people control interactive search? One type of decision that is made when performing a task such as searching the web is whether to continue to explore unattractive but immediately available links or to backup to previously experienced links. It has recently been suggested that this choice may be governed by a preset threshold. We report empirical evidence that in fact the choice is governed by memory for the quality of the unselected alternatives on previous pages. Further, we report a computational model that combines an instance- based memory for previous evaluations with display- driven action to control interactive search. Introduction Tasks such as web browsing and menu search are examples of what we call interactive search tasks. They differ from other problem solving tasks in that the effect of an operator is unknown until the operator has been implemented in the world. In these circumstances a problem solver cannot use mental lookahead in order to constrain search, rather search is constrained by two mutually dependent cognitive activities. First, people estimate the relative likelihoods that operators will lead to the goal and trade these off against estimates of cost (Pirolli and Card, 1999). In interactive search, estimates of likelihood are typically based on an interpretation of the relationship between the goal and the semantics of the word(s) and icon(s) used to represent the operator. Estimates of cost are often based on the time that operators are expected to take to implement in the world. Second, the process of likelihood estimation must be embedded within a strategy for controlling search. A strategy typically defines policies for determining which operators are included in the set of those considered and policies for reducing or eliminating the probability that operators that have been tried before are redundantly reselected. Typically a strategy for interactive search will be supported by memory for which operators have already been tried on the current search (so that reselection can be avoided) and by memory for information about which operators lead to success or failure on previous trials (Howes, 1994). Howes and Payne (2001) have argued that these needs are not easily captured by current architectural theories of human cognition. A search strategy is required in addition to an ability to follow label semantics because in real menus and on real web pages, label semantics (and therefore estimates of likelihood) are rarely sufficient to guarantee that users will navigate directly to the location of a goal without some fruitless exploration of other parts of the search space. An understanding of the process by which people rank order operators must be complemented by a model of which they consider, how they remember which they have tried, and how they remember where to find them. Previous research on the strategies that people use to control exploration in these circumstances has emphasised that performance is often display-based. I.e. problem solving is constrained by the set of operators currently available on the display of the device (Howes and Young, 1996). The device display imposes constraints on the problem solving process that limit the cognitive costs of device use. Other research has indicated that judgements of what choices have been taken before are sometimes made on the basis of long-term representations of familiarity (Payne, Richardson, Howes, 2000). Other research has directly addressed the question of when users choose to ‘backup’ from a choice point. A ‘backup’ operator is a special kind of operator in interactive search in that the user knows that its effect is to return the user to the previous, higher, node in the tree (although the user may not know the content of this node). There are a number of types of backup in web browsing. The ‘Back’ button on a browser takes the user to the previous page in the recent history stack. A link labelled ‘back’ on a web page will typically take a user to a page one level higher in the site hierarchy (though this is not guaranteed). The differences between these operations are potentially interesting but for here we consider a generic backup where the two definitions are aligned. One answer to the question of when users choose to backup is that backups are selected when evaluations of all available forward moves fall below some threshold (Miller and Remington, 2001). In their model, Miller