{"id":{"repo_id":"mit","oai_identifier":"oai:dspace.mit.edu:1721.1/66415"},"canonical_url":"https://search.dev.ndltd.org/etd/mit/oai:dspace.mit.edu:1721.1/66415","repository":{"repo_id":"mit","name":"MIT","base_url":"https://dspace.mit.edu/oai/request"},"display":{"title":"Real-time futures graph tracking visualization and analysis tool","abstract":"A hybrid envisionment is a novel representation of a simulated state graph, specifying all possible states and transitions of the system, characterized by both qualitative and quantitative state variables. The Deep Green project creates a hybrid envisionment, called a futures graph, to depict all possible occurrences and outcomes of a combat engagement between friendly and enemy units on a battlefield. During combat, Al state estimation techniques are utilized to efficiently track the state of the battle in a futures graph, giving the commander an up-to-date analysis of what is taking place on the battlefield and how it the battle could turn out. Because state estimation of highly complex hybrid envisionments is a relatively unexplored and novel process, it is important to ensure that it is handled efficiently and accurately enough for usage on the field. This paper explores an approach for discerning the behavior in state estimation through the use of an analysis suite. By accompanying Deep Green state estimation with the analysis suite developed, estimation techniques could be benchmarked and analyzed over various implementations through both numerical and graphical metrics. The metrics generated greatly helped to improve the estimation algorithm over the course of its development.","abstract_html":"A hybrid envisionment is a novel representation of a simulated state graph, specifying all possible states and transitions of the system, characterized by both qualitative and quantitative state variables. The Deep Green project creates a hybrid envisionment, called a futures graph, to depict all possible occurrences and outcomes of a combat engagement between friendly and enemy units on a battlefield. During combat, Al state estimation techniques are utilized to efficiently track the state of the battle in a futures graph, giving the commander an up-to-date analysis of what is taking place on the battlefield and how it the battle could turn out. Because state estimation of highly complex hybrid envisionments is a relatively unexplored and novel process, it is important to ensure that it is handled efficiently and accurately enough for usage on the field. This paper explores an approach for discerning the behavior in state estimation through the use of an analysis suite. By accompanying Deep Green state estimation with the analysis suite developed, estimation techniques could be benchmarked and analyzed over various implementations through both numerical and graphical metrics. The metrics generated greatly helped to improve the estimation algorithm over the course of its development.","abstract_has_math":false,"creators":["Fahey, Joseph M"],"institution":"Massachusetts Institute of Technology","degree_name":null,"degree_level":null,"degree_discipline":null,"degree_department":"Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science.","school":null,"contributors":[],"advisors":["Soraya Stevens and Leslie Pack Kaelbling."],"committee_chairs":[],"committee_members":[],"year":2011,"date_issued":"2011","date_published":"2011","updated_at":"2026-07-22T22:21:55Z","subjects":["Electrical Engineering and Computer Science."],"languages":["eng"],"rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"rights_urls":["http://dspace.mit.edu/handle/1721.1/7582"],"identifier_entries":[]},"links":{"outbound_url":"http://hdl.handle.net/1721.1/66415","outbound_label":"Handle","outbound_source":"dc:identifier.uri"},"metadata_groups":[{"id":"people","label":"People","entries":[{"key":"dc:contributor.advisor","label":"Advisor","values":["Soraya Stevens and Leslie Pack Kaelbling."]},{"key":"dc:contributor.department","label":"Department","values":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."]},{"key":"dc:contributor.other","label":"Dc Contributor Other","values":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."]},{"key":"dc:creator","label":"Author","values":["Fahey, Joseph M"]}]},{"id":"academic_context","label":"Academic Context","entries":[{"key":"dc:date.accessioned","label":"Dc Date Accessioned","values":["2011-10-17T21:23:30Z"]},{"key":"dc:date.available","label":"Dc Date Available","values":["2011-10-17T21:23:30Z"]},{"key":"dc:date.issued","label":"Date","values":["2011"]},{"key":"dc:publisher","label":"Institution","values":["Massachusetts Institute of Technology"]},{"key":"dc:type","label":"Dc Type","values":["Thesis"]}]},{"id":"subjects_keywords","label":"Subjects and Keywords","entries":[{"key":"dc:subject","label":"Dc Subject","values":["Electrical Engineering and Computer Science."]}]},{"id":"language_rights","label":"Language and Rights","entries":[{"key":"dc:language.iso","label":"Language (ISO)","values":["eng"]},{"key":"dc:rights","label":"Dc Rights","values":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."]},{"key":"dc:rights.uri","label":"Rights URI","values":["http://dspace.mit.edu/handle/1721.1/7582"]}]},{"id":"identifiers","label":"Identifiers","entries":[{"key":"dc:identifier.uri","label":"Identifier URI","values":["http://hdl.handle.net/1721.1/66415"]}]},{"id":"additional","label":"Additional Metadata","entries":[{"key":"dc:description","label":"Description","values":["Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.","Cataloged from PDF version of thesis.","Includes bibliographical references (p. 34-35)."]},{"key":"dc:description.abstract","label":"Abstract","values":["A hybrid envisionment is a novel representation of a simulated state graph, specifying all possible states and transitions of the system, characterized by both qualitative and quantitative state variables. The Deep Green project creates a hybrid envisionment, called a futures graph, to depict all possible occurrences and outcomes of a combat engagement between friendly and enemy units on a battlefield. During combat, Al state estimation techniques are utilized to efficiently track the state of the battle in a futures graph, giving the commander an up-to-date analysis of what is taking place on the battlefield and how it the battle could turn out. Because state estimation of highly complex hybrid envisionments is a relatively unexplored and novel process, it is important to ensure that it is handled efficiently and accurately enough for usage on the field. This paper explores an approach for discerning the behavior in state estimation through the use of an analysis suite. By accompanying Deep Green state estimation with the analysis suite developed, estimation techniques could be benchmarked and analyzed over various implementations through both numerical and graphical metrics. The metrics generated greatly helped to improve the estimation algorithm over the course of its development."]},{"key":"dc:description.degree","label":"Dc Description Degree","values":["M.Eng."]},{"key":"dc:title","label":"Title","values":["Real-time futures graph tracking visualization and analysis tool"]}]}],"canonical_facts":{"dc:contributor.advisor":["Soraya Stevens and Leslie Pack Kaelbling."],"dc:contributor.department":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:contributor.other":["Massachusetts Institute of Technology. Dept. of Electrical Engineering and Computer Science."],"dc:creator":["Fahey, Joseph M"],"dc:date.accessioned":["2011-10-17T21:23:30Z"],"dc:date.available":["2011-10-17T21:23:30Z"],"dc:date.issued":["2011"],"dc:description":["Thesis (M. Eng.)--Massachusetts Institute of Technology, Dept. of Electrical Engineering and Computer Science, 2011.","Cataloged from PDF version of thesis.","Includes bibliographical references (p. 34-35)."],"dc:description.abstract":["A hybrid envisionment is a novel representation of a simulated state graph, specifying all possible states and transitions of the system, characterized by both qualitative and quantitative state variables. The Deep Green project creates a hybrid envisionment, called a futures graph, to depict all possible occurrences and outcomes of a combat engagement between friendly and enemy units on a battlefield. During combat, Al state estimation techniques are utilized to efficiently track the state of the battle in a futures graph, giving the commander an up-to-date analysis of what is taking place on the battlefield and how it the battle could turn out. Because state estimation of highly complex hybrid envisionments is a relatively unexplored and novel process, it is important to ensure that it is handled efficiently and accurately enough for usage on the field. This paper explores an approach for discerning the behavior in state estimation through the use of an analysis suite. By accompanying Deep Green state estimation with the analysis suite developed, estimation techniques could be benchmarked and analyzed over various implementations through both numerical and graphical metrics. The metrics generated greatly helped to improve the estimation algorithm over the course of its development."],"dc:description.degree":["M.Eng."],"dc:identifier.uri":["http://hdl.handle.net/1721.1/66415"],"dc:language.iso":["eng"],"dc:publisher":["Massachusetts Institute of Technology"],"dc:rights":["M.I.T. theses are protected by copyright. They may be viewed from this source for any purpose, but reproduction or distribution in any format is prohibited without written permission. See provided URL for inquiries about permission."],"dc:rights.uri":["http://dspace.mit.edu/handle/1721.1/7582"],"dc:subject":["Electrical Engineering and Computer Science."],"dc:title":["Real-time futures graph tracking visualization and analysis tool"],"dc:type":["Thesis"]},"updated_at":"2026-07-22T22:21:55Z"}