In this paper we examine the notion of adaptive user interfaces, interactive systems that
invoke machine learning to improve their interaction with humans. We review some previous …

Learning from preferences, which provide means for expressing a subject's desires,
constitutes an important topic in machine learning research. This paper presents a …

We present PLIANT, a learning system that supports adaptive assistance in an open
calendaring system. PLIANT learns user preferences from the feedback that naturally occurs …

Reminder systems support people with impaired prospective memory and/or executive
function, by providing them with reminders of their functional daily activities. We integrate …

In many optimization and decision problems the objective function can be expressed as a
linear combination of competing criteria, the weights of which specify the relative importance …

This work presents a set of protocols for scheduling a meeting among agents that represent
their respective user's interests. Four protocols are discussed: a) the full information protocol …

In this paper, I discuss some varieties of explanation that can arise in intelligent agents. I
distinguish between process accounts, which address the detailed decisions made during …

The Stock Tracker is an adaptive recommendation system for trading stocks that
automatically acquires content-based models of user preferences to tailor its buy and sell …

Many calendar tools have become available to organize, display, and track a user's
commitments. However, most people still spend a considerable amount of time personally …

In this paper we propose a novel idea for adaptation of the user interface in complex
supervisory tasks. Under the assumption that the user behavior is stationary and that the …