{"id":389849,"date":"2017-06-11T05:33:34","date_gmt":"2017-06-11T12:33:34","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/?post_type=msr-research-item&p=389849"},"modified":"2020-09-28T05:30:14","modified_gmt":"2020-09-28T12:30:14","slug":"spontaneous-interactions-virtually-embodied-intelligent-assistant-minecraft","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/spontaneous-interactions-virtually-embodied-intelligent-assistant-minecraft\/","title":{"rendered":"Spontaneous Interactions with a Virtually Embodied Intelligent Assistant in Minecraft"},"content":{"rendered":"

An increasing number of our technological interactions are mediated through virtually embodied characters and software agents powered by machine learning. To understand how users relate to and evaluate these types of interfaces, we designed a Wizard of Oz prototype of an embodied agent in Minecraft that learns from users’ actions, and conducted a user study with 18 school-aged Minecraft players. We categorised nine main ways users spontaneously attempted to interact with and teach the agent: four using game controls, and five using natural language text input. This study lays groundwork for a better understanding of human interaction with learning agents in virtual worlds.<\/p>\n","protected":false},"excerpt":{"rendered":"

An increasing number of our technological interactions are mediated through virtually embodied characters and software agents powered by machine learning. To understand how users relate to and evaluate these types of interfaces, we designed a Wizard of Oz prototype of an embodied agent in Minecraft that learns from users’ actions, and conducted a user study […]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"footnotes":""},"msr-content-type":[3],"msr-research-highlight":[],"research-area":[13556,13554],"msr-publication-type":[193716],"msr-product-type":[],"msr-focus-area":[],"msr-platform":[],"msr-download-source":[],"msr-locale":[268875],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-389849","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"ACM - Association for 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