Option-Driven Design: Context, Tradeoffs, and Considerations for Accessibility

04/18/2023
by   Frank Elavsky, et al.
0

In Option-Driven Design, users must interact with options and settings for systems to adapt to their needs. This approach places the burden on both the user and the system to make the interaction between user and system fit. The user must know and find which options they need and then adjust them. In addition, the system must be capable of robust change, similar to system change in ability-based design. In this micro-paper I outline the context for option-driven design, followed by several design negotiations, tradeoffs, and suggestions worth considering with this approach.

READ FULL TEXT

page 1

page 2

research
01/07/2022

Attention Option-Critic

Temporal abstraction in reinforcement learning is the ability of an agen...
research
10/23/2020

Origins of Algorithmic Instabilities in Crowdsourced Ranking

Crowdsourcing systems aggregate decisions of many people to help users q...
research
08/22/2017

Reinforcement Learning in POMDPs with Memoryless Options and Option-Observation Initiation Sets

Many real-world reinforcement learning problems have a hierarchical natu...
research
03/02/2022

Delegated Online Search

In a delegation problem, a principal P with commitment power tries to pi...
research
09/19/2023

Evaluating the Benefits: Quantifying the Effects of TCP Options, QUIC, and CDNs on Throughput

To keep up with increasing demands on quality of experience, assessing a...
research
05/14/2020

Information Design for Congested Social Services: Optimal Need-Based Persuasion

We study the effectiveness of information design in reducing congestion ...
research
12/30/2022

E-commerce users' preferences for delivery options

Many e-commerce marketplaces offer their users fast delivery options for...

Please sign up or login with your details

Forgot password? Click here to reset