Adaptive aggregation methods for infinite horizon dynamic programming
A class of iterative aggregation algorithms for solving infinite horizon dynamic programming problems is proposed. The idea is to interject aggregation iterations in the course of the usual successive approximation method. An important feature that sets this method apart from earlier ones is that th...
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Veröffentlicht in: | IEEE transactions on automatic control 1989-06, Vol.34 (6), p.589-598 |
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container_title | IEEE transactions on automatic control |
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creator | Bertsekas, D.P. Castanon, D.A. |
description | A class of iterative aggregation algorithms for solving infinite horizon dynamic programming problems is proposed. The idea is to interject aggregation iterations in the course of the usual successive approximation method. An important feature that sets this method apart from earlier ones is that the aggregate groups of states change adaptively from one aggregation iteration to the next, depending on the progress of the computation. This allows acceleration of convergence in difficult problems involving multiple-ergodic classes for which methods using fixed groups of aggregate states are ineffective. No knowledge of special problem structure is utilized by the algorithms.< > |
doi_str_mv | 10.1109/9.24227 |
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The idea is to interject aggregation iterations in the course of the usual successive approximation method. An important feature that sets this method apart from earlier ones is that the aggregate groups of states change adaptively from one aggregation iteration to the next, depending on the progress of the computation. This allows acceleration of convergence in difficult problems involving multiple-ergodic classes for which methods using fixed groups of aggregate states are ineffective. No knowledge of special problem structure is utilized by the algorithms.< ></description><subject>Aggregates</subject><subject>Applied sciences</subject><subject>Approximation methods</subject><subject>Computer science; control theory; systems</subject><subject>Control theory. Systems</subject><subject>Convergence</subject><subject>Cost function</subject><subject>Dynamic programming</subject><subject>Equations</subject><subject>Exact sciences and technology</subject><subject>Infinite horizon</subject><subject>Iterative algorithms</subject><subject>Iterative methods</subject><subject>Optimal control</subject><subject>System theory</subject><issn>0018-9286</issn><issn>1558-2523</issn><fulltext>true</fulltext><rsrctype>article</rsrctype><creationdate>1989</creationdate><recordtype>article</recordtype><recordid>eNqNkM1LwzAYxoMoOKd49taD6Kmaz6Y5jjE_YOBFz-FdmnSRNp1JJ8y_3s6OnT29vDw_fg88CF0T_EAIVo_qgXJK5QmaECHKnArKTtEEY1LmipbFObpI6XN4C87JBC1mFWx6_20zqOtoa-h9F7LW9uuuSpnrYuaD88H3Nlt30f8MYbUL0HqTbWJXR2hbH-pLdOagSfbqcKfo42nxPn_Jl2_Pr_PZMjesEP3Q7xgTzFQYK8UrabBZKQFcCK64KIwqSyGx5ADWKVe5QoIgBuTKuJXFwNgU3Y3eoftra1OvW5-MbRoIttsmTUtFsJTkHyAVmBM6gPcjaGKXUrROb6JvIe40wXq_p1b6b8-BvD0oIRloXIRgfDrikhWE4z12M2LeWntMR8UvhVV8fA</recordid><startdate>19890601</startdate><enddate>19890601</enddate><creator>Bertsekas, D.P.</creator><creator>Castanon, D.A.</creator><general>IEEE</general><general>Institute of Electrical and Electronics Engineers</general><scope>IQODW</scope><scope>AAYXX</scope><scope>CITATION</scope><scope>7SC</scope><scope>7SP</scope><scope>7TB</scope><scope>8FD</scope><scope>FR3</scope><scope>JQ2</scope><scope>L7M</scope><scope>L~C</scope><scope>L~D</scope><scope>H8D</scope></search><sort><creationdate>19890601</creationdate><title>Adaptive aggregation methods for infinite horizon dynamic programming</title><author>Bertsekas, D.P. ; Castanon, D.A.</author></sort><facets><frbrtype>5</frbrtype><frbrgroupid>cdi_FETCH-LOGICAL-c365t-92f3353cd00994d7c0cb95a45549456c98857074aaef9fdf67a51ca7bcfbe0a33</frbrgroupid><rsrctype>articles</rsrctype><prefilter>articles</prefilter><language>eng</language><creationdate>1989</creationdate><topic>Aggregates</topic><topic>Applied sciences</topic><topic>Approximation methods</topic><topic>Computer science; control theory; systems</topic><topic>Control theory. Systems</topic><topic>Convergence</topic><topic>Cost function</topic><topic>Dynamic programming</topic><topic>Equations</topic><topic>Exact sciences and technology</topic><topic>Infinite horizon</topic><topic>Iterative algorithms</topic><topic>Iterative methods</topic><topic>Optimal control</topic><topic>System theory</topic><toplevel>peer_reviewed</toplevel><toplevel>online_resources</toplevel><creatorcontrib>Bertsekas, D.P.</creatorcontrib><creatorcontrib>Castanon, D.A.</creatorcontrib><collection>Pascal-Francis</collection><collection>CrossRef</collection><collection>Computer and Information Systems Abstracts</collection><collection>Electronics & Communications Abstracts</collection><collection>Mechanical & Transportation Engineering Abstracts</collection><collection>Technology Research Database</collection><collection>Engineering Research Database</collection><collection>ProQuest Computer Science Collection</collection><collection>Advanced Technologies Database with Aerospace</collection><collection>Computer and Information Systems Abstracts Academic</collection><collection>Computer and Information Systems Abstracts Professional</collection><collection>Aerospace Database</collection><jtitle>IEEE transactions on automatic control</jtitle></facets><delivery><delcategory>Remote Search Resource</delcategory><fulltext>fulltext_linktorsrc</fulltext></delivery><addata><au>Bertsekas, D.P.</au><au>Castanon, D.A.</au><format>journal</format><genre>article</genre><ristype>JOUR</ristype><atitle>Adaptive aggregation methods for infinite horizon dynamic programming</atitle><jtitle>IEEE transactions on automatic control</jtitle><stitle>TAC</stitle><date>1989-06-01</date><risdate>1989</risdate><volume>34</volume><issue>6</issue><spage>589</spage><epage>598</epage><pages>589-598</pages><issn>0018-9286</issn><eissn>1558-2523</eissn><coden>IETAA9</coden><abstract>A class of iterative aggregation algorithms for solving infinite horizon dynamic programming problems is proposed. The idea is to interject aggregation iterations in the course of the usual successive approximation method. An important feature that sets this method apart from earlier ones is that the aggregate groups of states change adaptively from one aggregation iteration to the next, depending on the progress of the computation. This allows acceleration of convergence in difficult problems involving multiple-ergodic classes for which methods using fixed groups of aggregate states are ineffective. No knowledge of special problem structure is utilized by the algorithms.< ></abstract><cop>New York, NY</cop><pub>IEEE</pub><doi>10.1109/9.24227</doi><tpages>10</tpages><oa>free_for_read</oa></addata></record> |
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subjects | Aggregates Applied sciences Approximation methods Computer science control theory systems Control theory. Systems Convergence Cost function Dynamic programming Equations Exact sciences and technology Infinite horizon Iterative algorithms Iterative methods Optimal control System theory |
title | Adaptive aggregation methods for infinite horizon dynamic programming |
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