Show simple item record

dc.contributor.authorUllman, Tomer David
dc.contributor.authorTenenbaum, Joshua B.
dc.contributor.authorBaker, Christopher Lawrence
dc.contributor.authorMacindoe, Owen
dc.contributor.authorEvans, Owain Rhys
dc.contributor.authorGoodman, Noah D.
dc.date.accessioned2011-02-25T20:57:28Z
dc.date.available2011-02-25T20:57:28Z
dc.date.issued2009-12
dc.identifier.isbn9781615679119
dc.identifier.urihttp://hdl.handle.net/1721.1/61347
dc.description.abstractEveryday social interactions are heavily influenced by our snap judgments about others’ goals. Even young infants can infer the goals of intentional agents from observing how they interact with objects and other agents in their environment: e.g., that one agent is ‘helping’ or ‘hindering’ another’s attempt to get up a hill or open a box. We propose a model for how people can infer these social goals from actions, based on inverse planning in multiagent Markov decision problems (MDPs). The model infers the goal most likely to be driving an agent’s behavior by assuming the agent acts approximately rationally given environmental constraints and its model of other agents present. We also present behavioral evidence in support of this model over a simpler, perceptual cue-based alternative.en_US
dc.description.sponsorshipUnited States. Army Research Office (ARO MURI grant W911NF-08-1-0242)en_US
dc.description.sponsorshipUnited States. Air Force Office of Scientific Research (MURI grant FA9550-07-1-0075)en_US
dc.description.sponsorshipNational Science Foundation (U.S.) (Graduate Research Fellowship)en_US
dc.description.sponsorshipJames S. McDonnell Foundation (Collaborative Interdisciplinary Grant on Causal Reasoning)en_US
dc.language.isoen_US
dc.publisherNeural Information Processing Systems Foundationen_US
dc.relation.isversionofhttp://books.nips.cc/papers/files/nips22/NIPS2009_1192.pdf
dc.rightsAttribution-Noncommercial-Share Alike 3.0 Unporteden_US
dc.rights.urihttp://creativecommons.org/licenses/by-nc-sa/3.0/en_US
dc.sourceMIT web domainen_US
dc.titleHelp or hinder: Bayesian models of social goal inferenceen_US
dc.typeArticleen_US
dc.identifier.citationUllman, Tomer D., et al. "Help or Hinder: Bayesian Models of Social Goal Inference." Advances in Neural Information Processing Systems 22, Annual Conference on Neural Information Processing Systems, NIPS 2009.en_US
dc.contributor.departmentMassachusetts Institute of Technology. Department of Brain and Cognitive Sciencesen_US
dc.contributor.departmentMassachusetts Institute of Technology. School of Humanities, Arts, and Social Sciencesen_US
dc.contributor.approverTenenbaum, Joshua B.
dc.contributor.mitauthorUllman, Tomer David
dc.contributor.mitauthorTenenbaum, Joshua B.
dc.contributor.mitauthorBaker, Christopher Lawrence
dc.contributor.mitauthorMacindoe, Owen
dc.contributor.mitauthorEvans, Owain Rhys
dc.contributor.mitauthorGoodman, Noah D.
dc.relation.journalAdvances in Neural Information Processing Systems 22en_US
dc.eprint.versionAuthor's final manuscripten_US
dc.type.urihttp://purl.org/eprint/type/ConferencePaperen_US
dspace.orderedauthorsUllman, Tomer D.; Baker, Chris L.; Macindoe, Owen; Evans, Owain; Goodman, Noah D.; Tenenbaum, Joshua B.
dc.identifier.orcidhttps://orcid.org/0000-0002-1925-2035
dc.identifier.orcidhttps://orcid.org/0000-0002-9773-7871
dc.identifier.orcidhttps://orcid.org/0000-0001-7870-4487
dc.identifier.orcidhttps://orcid.org/0000-0003-1722-2382
mit.licenseOPEN_ACCESS_POLICYen_US
mit.metadata.statusComplete


Files in this item

Thumbnail

This item appears in the following Collection(s)

Show simple item record