منابع مشابه
A Study in Preference Elicitation under Uncertainty
In many areas of Artificial Intelligence (AI), we are interested in helping people make better decisions. This help can result in two advantages. First, computers can process large amounts of data and perform quick calculations, leading to better decisions. Second, if a user does not have to think about some decisions, they have more time to focus on other things they find important. Since user...
متن کاملCoordination with Communication under Oath
Herein we explore whether the social psychology theory of commitment via a truth-telling oath can reduce coordination failure. Using a classic sequential coordination game, we ask all players to sign voluntarily a truth-telling oath before playing the game with cheap-talk communication. Three results emerge with commitment-via-the-oath: (1) coordination increased by nearly 50 percent; (2) sende...
متن کاملUser-Involved Preference Elicitation
When searching for configurable products, helping users to state their preferences is a crucial task. It involves helping users to understand the space of feasible configurations to decide on realistic preferences. However, many computer tools do not afford users to adequately focus on fundamental decision objectives, reveal hidden preferences, revise conflicting preferences, or explicitly reas...
متن کاملConstructive Preference Elicitation
When faced with large or complex decision problems, human decision makers (DM) can make costly mistakes, due to inherent limitations of their memory, attention, and knowledge. Preference elicitation tools assist the decision maker in overcoming these limitations. They do so by interactively learning the DM’s preferences through appropriately chosen queries and suggesting high-quality outcomes b...
متن کاملGaussian Process Preference Elicitation
Bayesian approaches to preference elicitation (PE) are particularly attractive due to their ability to explicitly model uncertainty in users’ latent utility functions. However, previous approaches to Bayesian PE have ignored the important problem of generalizing from previous users to an unseen user in order to reduce the elicitation burden on new users. In this paper, we address this deficienc...
متن کاملذخیره در منابع من
با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید
ژورنال
عنوان ژورنال: SSRN Electronic Journal
سال: 2010
ISSN: 1556-5068
DOI: 10.2139/ssrn.1803658