{"id":168626,"date":"2015-07-28T00:00:00","date_gmt":"2015-07-28T00:00:00","guid":{"rendered":"https:\/\/www.microsoft.com\/en-us\/research\/msr-research-item\/towards-situated-activity-management-representation-inference-and-decision-making\/"},"modified":"2020-03-26T11:36:07","modified_gmt":"2020-03-26T18:36:07","slug":"towards-situated-activity-management-representation-inference-and-decision-making","status":"publish","type":"msr-research-item","link":"https:\/\/www.microsoft.com\/en-us\/research\/publication\/towards-situated-activity-management-representation-inference-and-decision-making\/","title":{"rendered":"Towards Situated Activity Management: Representation, Inference and Decision Making"},"content":{"rendered":"<div class=\"asset-content\">\n<p>We introduce and discuss the problem of <em>situated activity management<\/em>, and present an approach for guiding and coordinating an agent\u2019s speech and activities amidst the dynamics of evolving settings. Specifically, we couple a hierarchical representation of activities with a novel state tracking approach based on conditional Markov Networks. We show how the approach can enable an agent to reason jointly about parallel coordinated actions and the changing situational context. The hierarchical structure and joint inference allows for a modular authoring of rules used for making in-stream decisions. We have implemented a proof-of-concept for this approach and illustrate its functionality with a simulated dialog trace.<\/p>\n<\/div>\n<p><!-- .asset-content --><\/p>\n","protected":false},"excerpt":{"rendered":"<p>We introduce and discuss the problem of situated activity management, and present an approach for guiding and coordinating an agent\u2019s speech and activities amidst the dynamics of evolving settings. Specifically, we couple a hierarchical representation of activities with a novel state tracking approach based on conditional Markov Networks. We show how the approach can enable [&hellip;]<\/p>\n","protected":false},"featured_media":0,"template":"","meta":{"msr-url-field":"","msr-podcast-episode":"","msrModifiedDate":"","msrModifiedDateEnabled":false,"ep_exclude_from_search":false,"_classifai_error":"","msr-author-ordering":[{"type":"user_nicename","value":"Dan Bohus","user_id":"31581"},{"type":"user_nicename","value":"Ece Kamar","user_id":"31710"},{"type":"user_nicename","value":"Eric Horvitz","user_id":"32033"}],"msr_publishername":"","msr_publisher_other":"","msr_booktitle":"","msr_chapter":"","msr_edition":"","msr_editors":"","msr_how_published":"","msr_isbn":"","msr_issue":"","msr_journal":"","msr_number":"MSR-TR-2015-64","msr_organization":"Microsoft","msr_pages_string":"","msr_page_range_start":"","msr_page_range_end":"","msr_series":"","msr_volume":"","msr_copyright":"","msr_conference_name":"","msr_doi":"","msr_arxiv_id":"","msr_s2_paper_id":"","msr_mag_id":"","msr_pubmed_id":"","msr_other_authors":"","msr_other_contributors":"","msr_speaker":"","msr_award":"","msr_affiliation":"","msr_institution":"","msr_host":"","msr_version":"","msr_duration":"","msr_original_fields_of_study":"","msr_release_tracker_id":"","msr_s2_match_type":"","msr_citation_count_updated":"","msr_published_date":"2015-7-28","msr_highlight_text":"","msr_notes":"","msr_longbiography":"","msr_publicationurl":"","msr_external_url":"","msr_secondary_video_url":"","msr_conference_url":"","msr_journal_url":"","msr_s2_pdf_url":"","msr_year":0,"msr_citation_count":0,"msr_influential_citations":0,"msr_reference_count":0,"msr_s2_match_confidence":0,"msr_microsoftintellectualproperty":true,"msr_s2_open_access":false,"msr_s2_author_ids":[],"msr_pub_ids":[],"msr_hide_image_in_river":0,"footnotes":""},"msr-research-highlight":[],"research-area":[13556,13545,13554],"msr-publication-type":[193718],"msr-publisher":[],"msr-focus-area":[],"msr-locale":[268875],"msr-post-option":[],"msr-field-of-study":[],"msr-conference":[],"msr-journal":[],"msr-impact-theme":[],"msr-pillar":[],"class_list":["post-168626","msr-research-item","type-msr-research-item","status-publish","hentry","msr-research-area-artificial-intelligence","msr-research-area-human-language-technologies","msr-research-area-human-computer-interaction","msr-locale-en_us"],"msr_publishername":"","msr_edition":"","msr_affiliation":"","msr_published_date":"2015-7-28","msr_host":"","msr_duration":"","msr_version":"","msr_speaker":"","msr_other_contributors":"","msr_booktitle":"","msr_pages_string":"","msr_chapter":"","msr_isbn":"","msr_journal":"","msr_volume":"","msr_number":"MSR-TR-2015-64","msr_editors":"","msr_series":"","msr_issue":"","msr_organization":"Microsoft","msr_how_published":"","msr_notes":"","msr_highlight_text":"","msr_release_tracker_id":"","msr_original_fields_of_study":"","msr_download_urls":"","msr_external_url":"","msr_secondary_video_url":"","msr_longbiography":"","msr_microsoftintellectualproperty":1,"msr_main_download":"217072","msr_publicationurl":"","msr_doi":"","msr_publication_uploader":[{"type":"file","viewUrl":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2015\/07\/sigdial_11.pdf","id":"217072","title":"sigdial_11.pdf","label_id":"243109","label":0}],"msr_related_uploader":"","msr_citation_count":0,"msr_citation_count_updated":"","msr_s2_paper_id":"","msr_influential_citations":0,"msr_reference_count":0,"msr_arxiv_id":"","msr_s2_author_ids":[],"msr_s2_open_access":false,"msr_s2_pdf_url":null,"msr_attachments":[{"id":217072,"url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-content\/uploads\/2015\/07\/sigdial_11.pdf"}],"msr-author-ordering":[{"type":"user_nicename","value":"Dan Bohus","user_id":31581,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Dan Bohus"},{"type":"user_nicename","value":"Ece Kamar","user_id":31710,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Ece Kamar"},{"type":"user_nicename","value":"Eric Horvitz","user_id":32033,"rest_url":"https:\/\/www.microsoft.com\/en-us\/research\/wp-json\/microsoft-research\/v1\/researchers?person=Eric Horvitz"}],"msr_impact_theme":[],"msr_research_lab":[],"msr_event":[],"msr_group":[144633],"msr_project":[390800],"publication":[],"video":[],"msr-tool":[],"msr_publication_type":"techreport","related_content":{"projects":[{"ID":390800,"post_title":"Situated Interaction","post_name":"situated-interaction","post_type":"msr-project","post_date":"2017-07-07 12:00:28","post_modified":"2021-04-06 15:07:38","post_status":"publish","permalink":"https:\/\/www.microsoft.com\/en-us\/research\/project\/situated-interaction\/","post_excerpt":"The situated interaction research effort aims to enable computers to reason more deeply about their surroundings, and engage in fluid interaction with humans in physically situated settings. When people interact with each other, they engage in a rich, highly coordinated, mixed-initiative process, regulated through both verbal and non-verbal channels. In contrast, while their perceptual abilities are improving, computers are still unaware of their physical surroundings and of the \u201cphysics\u201d of human interaction. 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