Paper Info
Title
Generating automated predictions of behavior strategically adapted to specific performance objectives
Abstract
It has been well established in Cognitive Psychology that humans are able to strategically adapt performance, even highly skilled performance, to meet explicit task goals such as being accurate (rather than fast). This paper describes a new capability for generating multiple human performance predictions from a single task specification as a function of different performance objective functions. As a demonstration of this capability, the Cognitive Constraint Modeling approach was used to develop models for several tasks across two interfaces from the aviation domain. Performance objectives are explicitly declared as part of the model, and the CORE (Constraint-based Optimal Reasoning Engine) architecture itself formally derives the detailed strategies that are maximally adapted to these objectives. The models are analyzed for emergent strategic variation, comparing those optimized for task time with those optimized for working memory load. The approach has potential application in user interface and procedure design.
Year
DOI
Venue
2006
10.1145/1124772.1124866
CHI
Keywords
Field
DocType
new capability,generating automated prediction,cognitive constraint modeling approach,task time,multiple human performance prediction,different performance objective function,cognitive psychology,single task specification,skilled performance,performance objective,specific performance objective,explicit task goal,working memory,user model,user interface,user modeling,human performance,objective function
Specific performance,Architecture,Semantic reasoner,Computer science,Working memory,Aviation,Human–computer interaction,User modeling,User interface,Cognition
Conference
ISBN
Citations 
PageRank 
1-59593-372-7
11
1.40
References 
Authors
9
6
Name
Order
Citations
PageRank
Katherine Eng116511.89
Richard L. Lewis241526.02
Irene Tollinger3373.81
Alina Chu4111.40
Andrew Howes5424.39
Alonso H. Vera628854.58