Zero-Shot Linear Combinations of Grounded Social Interactions with Linear Social MDPs
نویسندگان
چکیده
Humans and animals engage in rich social interactions. It is often theorized that a relatively small number of basic interactions give rise to the full range behavior observed. But no computational theory explaining how combine together has been proposed before. We do so here. take model, Social MDP, which able express interactions, extend it represent linear combinations Practically for robotics applications, such models are now not just an agent should help another agent, but goal-centric Perhaps helping someone get dressed, preventing them from falling, happy exchange stories meantime. How responds socially, depend on what thinks other doing at point time. To encode this notion, we as defined MDPs, compute weights those fly depending estimated goals agents. This new Linear enables zero-shot reasoning about complex provides mathematical basis long-standing intuition compose, leads interesting behaviors validate using human observers. Complex part future intelligent agents, having principled built foundation like MDPs will make possible bring every robotic application.
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Financial support has been supplied to Blume by NSF grant CCF-0910940 and by WWTF Grant “Die Evolution von Normen und Konventionen in der Wirtschaft”, Brock and Durlauf by the Vilas Professorship, and Durlauf by the University of Wisconsin Graduate School, Laurits Christensen Chair in Economics, and Institute for New Economic Thinking, all of which is greatly appreciated. Hon Ho Kwok and Xiangr...
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ژورنال
عنوان ژورنال: Proceedings of the ... AAAI Conference on Artificial Intelligence
سال: 2023
ISSN: ['2159-5399', '2374-3468']
DOI: https://doi.org/10.1609/aaai.v37i1.25080