Abstract: Designing user interfaces includes categorizing users, by at least one processor, into a predetermined number of behaviorally distinct groups each specified by behavioral characteristics. The users are re-categorized, by the at least one processor, into the predetermined number of new behaviorally distinct groups each specified by revised behavioral characteristics. The user interfaces are designed, by the at least one processor, based on describing and modeling at least one of the re-categorized users and the new behaviorally distinct groups.

Abstract: Designing user interfaces includes categorizing users, by at least one processor, into a predetermined number of behaviorally distinct groups each specified by behavioral characteristics. The users are re-categorized, by the at least one processor, into the predetermined number of new behaviorally distinct groups each specified by revised behavioral characteristics. The user interfaces are designed, by the at least one processor, based on describing and modeling at least one of the re-categorized users and the new behaviorally distinct groups.

Abstract: Designing user interfaces for users in a user population includes modeling behaviorally distinct groups of the users and customizing the user interfaces based on either or both interactive testing by the users and modeling the behaviorally distinct groups of the users. The user population is categorized into the behaviorally distinct groups of the users based on predetermined characteristics and behaviors for the users.

Abstract: Designing user interfaces for users in a user population includes modeling behaviorally distinct groups of the users and customizing the user interfaces based on either or both interactive testing by the users and modeling the behaviorally distinct groups of the users. The user population is categorized into the behaviorally distinct groups of the users based on predetermined characteristics and behaviors for the users.

Abstract: A method that incorporates a detailed, precise procedure of designing a user interface by utilizing agent behavioral models. This method applies quantitative and qualitative agent behavioral models derived through the Categorize Describe-Model (CDM) methodology to the iterative design stage of interface development. The method includes: (1) categorizing at least two users; (2) validating targeted user behaviors and preferences; (3) capturing emergent behaviors and preferences; (4) tracking design requirements and implementations; (5) accommodating diversity in performance and preference during interactive testing; and (6) customizing a user interface design to each of the at least two users.

Abstract: A method that incorporates a detailed, precise procedure of designing a user interface by utilizing agent behavioral models. This method applies quantitative and qualitative agent behavioral models derived through the Categorize Describe-Model (CDM) methodology to the iterative design stage of interface development. The method includes: (1) categorizing at least two users; (2) validating targeted user behaviors and preferences; (3) capturing emergent behaviors and preferences; (4) tracking design requirements and implementations; (5) accommodating diversity in performance and preference during interactive testing; and (6) customizing a user interface design to each of the at least two users.

Abstract: A method that incorporates a detailed, precise procedure of designing a user interface by utilizing agent behavioral models. This method applies quantitative and qualitative agent behavioral models derived through the Categorize Describe-Model (CDM) methodology to the iterative design stage of interface development. The method includes: (1) categorizing at least two users; (2) validating targeted user behaviors and preferences; (3) capturing emergent behaviors and preferences; (4) tracking design requirements and implementations; (5) accommodating diversity in performance and preference during interactive testing; and (6) customizing a user interface design to each of the at least two users.

Abstract: System and methods for intelligent routing of requests from customers to agents where a request is received at a service center from a customer. Identification information related to the customer is accessed. Background information on the customer is retrieved from a storage facility. Task and attitude information about the customer is gathered. A model of the customer is created. Models for at least two agents are created. A performance optimizing calculation is performed that matches the customer model and the models for the at least two agents. A best match agent from the at least two agents is determined based on the matching. The customer request is routed to the best match agent.