People often have reciprocal habits, almost auto- matically responding to others’ actions. A robot who interacts with humans may also reciprocate, in order to come across natural and be predictable. We aim to facilitate decision sup- port that advises on utility-efficient habits in these interac- tions. To this end, given a model for reciprocation behavior with parameters that represent habits, we define a game that describes what habit one should adopt to increase the utility of the process. This paper concentrates on two agents. The used model defines that an agent’s action is a weighted com- bination of the other’s previous actions (reacting) and either i) her innate kindness, or ii) her own previous action (inertia). In order to analyze what happens when everyone reciprocates rationally, we define a game where an agent may choose her habit, which is either her reciprocation attitude (i or ii), or both her reciprocation attitude and weight. We characterize the Nash equilibria of these games and consider their effi- ciency. We find that the less kind agents should adjust to the kinder agents to improve both their own utility as well as the social welfare. This constitutes advice on improving coopera- tion and explains real life phenomena in human interaction, such as the societal benefits from adopting the behavior of the kindest person, or becoming more polite as one grows up.
Original languageEnglish
Title of host publicationECAI 2016
Subtitle of host publication22nd European Conference on Artificial Intelligence
EditorsGal A. Kaminka, Maria Fox, Paolo Bouquet, Eyke Hüllermeier, Virginia Dignum, Frank Dignum, Frank van Harmelen
PublisherIOS Press
Number of pages9
ISBN (Electronic)978-1-61499-672-9
ISBN (Print)978-1-61499-671-2
Publication statusPublished - 2016
EventECAI 2016: 22nd European Conference on Artificial Intelligence 2016 - World Forum, The Hague, Netherlands
Duration: 29 Aug 20162 Sep 2016
Conference number: 22

Publication series

NameFrontiers in Artificial Intelligence and Applications
PublisherIOS Press
ISSN (Print)0922-6389
ISSN (Electronic)1879-8314


ConferenceECAI 2016
Abbreviated titleECAI 2016
CityThe Hague
OtherIncluding Prestigious Applications of Artificial Intelligence, PAIS 2016
Internet address

ID: 10532998