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dc.contributor.authorWilliams, Brian C.en_US
dc.contributor.authorSullivan, Gregen_US
dc.coverage.temporalFall 2003en_US
dc.date.issued2003-12
dc.identifier16.410-Fall2003
dc.identifierlocal: 16.410
dc.identifierlocal: 16.413
dc.identifierlocal: IMSCP-MD5-d2d8e869ee4b551db620ce34ccbba524
dc.identifier.urihttp://hdl.handle.net/1721.1/36896
dc.description.abstractThis course surveys a variety of reasoning, optimization, and decision-making methodologies for creating highly autonomous systems and decision support aids. The focus is on principles, algorithms, and their applications, taken from the disciplines of artificial intelligence and operations research. Reasoning paradigms include logic and deduction, heuristic and constraint-based search, model-based reasoning, planning and execution, reasoning under uncertainty, and machine learning. Optimization paradigms include linear, integer and dynamic programming. Decision-making paradigms include decision theoretic planning, and Markov decision processes. This course is offered both to undergraduate (16.410) students as a professional area undergraduate subject, in the field of aerospace information technology, and graduate (16.413) students.en_US
dc.languageen-USen_US
dc.rights.uriUsage Restrictions: This site (c) Massachusetts Institute of Technology 2003. Content within individual courses is (c) by the individual authors unless otherwise noted. The Massachusetts Institute of Technology is providing this Work (as defined below) under the terms of this Creative Commons public license ("CCPL" or "license"). The Work is protected by copyright and/or other applicable law. Any use of the work other than as authorized under this license is prohibited. By exercising any of the rights to the Work provided here, You (as defined below) accept and agree to be bound by the terms of this license. The Licensor, the Massachusetts Institute of Technology, grants You the rights contained here in consideration of Your acceptance of such terms and conditions.en_US
dc.subjectdecision-makingen_US
dc.subjectreasoningen_US
dc.subjectautonomous systemsen_US
dc.subjectdecision supporten_US
dc.subjectalgorithmsen_US
dc.subjectartificial intelligenceen_US
dc.subjecta.i.en_US
dc.subjectoperations researchen_US
dc.subjectlogicen_US
dc.subjectdeductionen_US
dc.subjectheuristic searchen_US
dc.subjectconstraint-based searchen_US
dc.subjectmodel-based reasoningen_US
dc.subjectplanningen_US
dc.subjectexecutionen_US
dc.subjectuncertaintyen_US
dc.subjectmachine learningen_US
dc.subjectlinear programmingen_US
dc.subjectdynamic programmingen_US
dc.subjectinteger programmingen_US
dc.subjectnetwork optimizationen_US
dc.subjectdecision analysisen_US
dc.subjectdecision theoretic planningen_US
dc.subjectMarkov decision processen_US
dc.subjectschemeen_US
dc.subjectpropositional logicen_US
dc.subjectconstraintsen_US
dc.subjectMarkov processesen_US
dc.subjectcomputational performanceen_US
dc.subjectsatisfactionen_US
dc.subjectlearning algorithmsen_US
dc.subjectsystem stateen_US
dc.subjectstateen_US
dc.subjectplan spacesen_US
dc.subjectmodel theoryen_US
dc.subjectdecision treesen_US
dc.subjectfunction approximatorsen_US
dc.subjectoptimization algorithmsen_US
dc.subjectlimitationsen_US
dc.subjecttradeoffsen_US
dc.subjectsearch and reasoningen_US
dc.subjectgame tree searchen_US
dc.subjectlocal stochastic searchen_US
dc.subjectstochasticen_US
dc.subjectgenetic algorithmsen_US
dc.subjectconstraint satisfactionen_US
dc.subjectpropositional inferenceen_US
dc.subjectrule-based systemsen_US
dc.subjectmodel-based diagnosisen_US
dc.subjectneural netsen_US
dc.subjectreinforcement learningen_US
dc.subjectweb-baseden_US
dc.subjectautonomyen_US
dc.subjectsearch treesen_US
dc.subject16.410en_US
dc.subject16.413en_US
dc.subjectDecision makingen_US
dc.title16.410 / 16.413 Principles of Autonomy and Decision Making, Fall 2003en_US
dc.title.alternativePrinciples of Autonomy and Decision Makingen_US


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