Advice Provision in Multiple Prospect Selection Problems

Amos Azaria, Sarit Kraus
2013 PROCEEDINGS OF THE THIRTIETH AAAI CONFERENCE ON ARTIFICIAL INTELLIGENCE AND THE TWENTY-EIGHTH INNOVATIVE APPLICATIONS OF ARTIFICIAL INTELLIGENCE CONFERENCE  
When humans face a broad spectrum of topics, where each topic consists of several options, they usually make a decision on each topic separately. Usually, a person will perform better by making a global decision, however, taking all consequences into account is extremely difficult. We present a novel computational method for advice-generation in an environment where people need to decide among multiple selection problems. This method is based on the prospect theory and uses machine learning
more » ... niques. We graphically present this advice to the users and compare it with an advice which encourages the users to always select the option with a higher expected outcome. We show that our method outperforms the expected outcome approach in terms of user happiness and satisfaction.
doi:10.1609/aaai.v27i1.8523 fatcat:eq32eusbyjck5gsk3yiy7woaq4