Stochastic global maximum principle for optimization with recursive utilities View Full Text


Ontology type: schema:ScholarlyArticle      Open Access: True


Article Info

DATE

2017-12

AUTHORS

Mingshang Hu

ABSTRACT

In this paper, we study the recursive stochastic optimal control problems. The control domain does not need to be convex, and the generator of the backward stochastic differential equation can contain z. We obtain the variational equations for backward stochastic differential equations, and then obtain the maximum principle which solves completely Peng’s open problem. More... »

PAGES

1

References to SciGraph publications

Identifiers

URI

http://scigraph.springernature.com/pub.10.1186/s41546-017-0014-7

DOI

http://dx.doi.org/10.1186/s41546-017-0014-7

DIMENSIONS

https://app.dimensions.ai/details/publication/pub.1083720146


Indexing Status Check whether this publication has been indexed by Scopus and Web Of Science using the SN Indexing Status Tool
Incoming Citations Browse incoming citations for this publication using opencitations.net

JSON-LD is the canonical representation for SciGraph data.

TIP: You can open this SciGraph record using an external JSON-LD service: JSON-LD Playground Google SDTT

[
  {
    "@context": "https://springernature.github.io/scigraph/jsonld/sgcontext.json", 
    "about": [
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/0102", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Applied Mathematics", 
        "type": "DefinedTerm"
      }, 
      {
        "id": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/01", 
        "inDefinedTermSet": "http://purl.org/au-research/vocabulary/anzsrc-for/2008/", 
        "name": "Mathematical Sciences", 
        "type": "DefinedTerm"
      }
    ], 
    "author": [
      {
        "affiliation": {
          "alternateName": "Shandong University", 
          "id": "https://www.grid.ac/institutes/grid.27255.37", 
          "name": [
            "Zhongtai Institute of Finance, Shandong University, Jinan, 250100, Shandong, People\u2019s Republic of China"
          ], 
          "type": "Organization"
        }, 
        "familyName": "Hu", 
        "givenName": "Mingshang", 
        "id": "sg:person.014520253357.48", 
        "sameAs": [
          "https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014520253357.48"
        ], 
        "type": "Person"
      }
    ], 
    "citation": [
      {
        "id": "https://doi.org/10.1016/j.automatica.2013.02.005", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1011815320"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://app.dimensions.ai/details/publication/pub.1013764448", 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1466-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013764448", 
          "https://doi.org/10.1007/978-1-4612-1466-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-1-4612-1466-3", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1013764448", 
          "https://doi.org/10.1007/978-1-4612-1466-3"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0304-4149(03)00089-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022087436"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/s0304-4149(03)00089-9", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1022087436"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/1467-9965.00022", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1023508949"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/978-0-387-35359-3_32", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1030292727", 
          "https://doi.org/10.1007/978-0-387-35359-3_32"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01195978", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035616904", 
          "https://doi.org/10.1007/bf01195978"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "sg:pub.10.1007/bf01195978", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1035616904", 
          "https://doi.org/10.1007/bf01195978"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1017/s0334270000007645", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043240724"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1006/jmaa.1999.6515", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1043700742"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0167-6911(90)90082-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048954288"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1016/0167-6911(90)90082-6", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1048954288"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1111/1468-0262.00337", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1049495435"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/0328054", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062844229"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/090763287", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062856460"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s0363012900374737", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062880431"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s0363012992233858", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062880915"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1137/s036301299834973x", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1062881519"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.1214/aoap/1015345345", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1064397436"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.2307/2951600", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1070145901"
        ], 
        "type": "CreativeWork"
      }, 
      {
        "id": "https://doi.org/10.4310/cis.2006.v6.n4.a4", 
        "sameAs": [
          "https://app.dimensions.ai/details/publication/pub.1072458441"
        ], 
        "type": "CreativeWork"
      }
    ], 
    "datePublished": "2017-12", 
    "datePublishedReg": "2017-12-01", 
    "description": "In this paper, we study the recursive stochastic optimal control problems. The control domain does not need to be convex, and the generator of the backward stochastic differential equation can contain z. We obtain the variational equations for backward stochastic differential equations, and then obtain the maximum principle which solves completely Peng\u2019s open problem.", 
    "genre": "research_article", 
    "id": "sg:pub.10.1186/s41546-017-0014-7", 
    "inLanguage": [
      "en"
    ], 
    "isAccessibleForFree": true, 
    "isPartOf": [
      {
        "id": "sg:journal.1290466", 
        "issn": [
          "2367-0126"
        ], 
        "name": "Probability, Uncertainty and Quantitative Risk", 
        "type": "Periodical"
      }, 
      {
        "issueNumber": "1", 
        "type": "PublicationIssue"
      }, 
      {
        "type": "PublicationVolume", 
        "volumeNumber": "2"
      }
    ], 
    "name": "Stochastic global maximum principle for optimization with recursive utilities", 
    "pagination": "1", 
    "productId": [
      {
        "name": "readcube_id", 
        "type": "PropertyValue", 
        "value": [
          "26ef6c0999b863a2abdd9103430b3c8150e0491377210c0790c5797b17507b18"
        ]
      }, 
      {
        "name": "doi", 
        "type": "PropertyValue", 
        "value": [
          "10.1186/s41546-017-0014-7"
        ]
      }, 
      {
        "name": "dimensions_id", 
        "type": "PropertyValue", 
        "value": [
          "pub.1083720146"
        ]
      }
    ], 
    "sameAs": [
      "https://doi.org/10.1186/s41546-017-0014-7", 
      "https://app.dimensions.ai/details/publication/pub.1083720146"
    ], 
    "sdDataset": "articles", 
    "sdDatePublished": "2019-04-11T12:27", 
    "sdLicense": "https://scigraph.springernature.com/explorer/license/", 
    "sdPublisher": {
      "name": "Springer Nature - SN SciGraph project", 
      "type": "Organization"
    }, 
    "sdSource": "s3://com-uberresearch-data-dimensions-target-20181106-alternative/cleanup/v134/2549eaecd7973599484d7c17b260dba0a4ecb94b/merge/v9/a6c9fde33151104705d4d7ff012ea9563521a3ce/jats-lookup/v90/0000000362_0000000362/records_87117_00000001.jsonl", 
    "type": "ScholarlyArticle", 
    "url": "https://link.springer.com/10.1186%2Fs41546-017-0014-7"
  }
]
 

Download the RDF metadata as:  json-ld nt turtle xml License info

HOW TO GET THIS DATA PROGRAMMATICALLY:

JSON-LD is a popular format for linked data which is fully compatible with JSON.

curl -H 'Accept: application/ld+json' 'https://scigraph.springernature.com/pub.10.1186/s41546-017-0014-7'

N-Triples is a line-based linked data format ideal for batch operations.

curl -H 'Accept: application/n-triples' 'https://scigraph.springernature.com/pub.10.1186/s41546-017-0014-7'

Turtle is a human-readable linked data format.

curl -H 'Accept: text/turtle' 'https://scigraph.springernature.com/pub.10.1186/s41546-017-0014-7'

RDF/XML is a standard XML format for linked data.

curl -H 'Accept: application/rdf+xml' 'https://scigraph.springernature.com/pub.10.1186/s41546-017-0014-7'


 

This table displays all metadata directly associated to this object as RDF triples.

119 TRIPLES      21 PREDICATES      46 URIs      19 LITERALS      7 BLANK NODES

Subject Predicate Object
1 sg:pub.10.1186/s41546-017-0014-7 schema:about anzsrc-for:01
2 anzsrc-for:0102
3 schema:author Nb6ffd362fbb9485b833ce8c7ca2059f7
4 schema:citation sg:pub.10.1007/978-0-387-35359-3_32
5 sg:pub.10.1007/978-1-4612-1466-3
6 sg:pub.10.1007/bf01195978
7 https://app.dimensions.ai/details/publication/pub.1013764448
8 https://doi.org/10.1006/jmaa.1999.6515
9 https://doi.org/10.1016/0167-6911(90)90082-6
10 https://doi.org/10.1016/j.automatica.2013.02.005
11 https://doi.org/10.1016/s0304-4149(03)00089-9
12 https://doi.org/10.1017/s0334270000007645
13 https://doi.org/10.1111/1467-9965.00022
14 https://doi.org/10.1111/1468-0262.00337
15 https://doi.org/10.1137/0328054
16 https://doi.org/10.1137/090763287
17 https://doi.org/10.1137/s0363012900374737
18 https://doi.org/10.1137/s0363012992233858
19 https://doi.org/10.1137/s036301299834973x
20 https://doi.org/10.1214/aoap/1015345345
21 https://doi.org/10.2307/2951600
22 https://doi.org/10.4310/cis.2006.v6.n4.a4
23 schema:datePublished 2017-12
24 schema:datePublishedReg 2017-12-01
25 schema:description In this paper, we study the recursive stochastic optimal control problems. The control domain does not need to be convex, and the generator of the backward stochastic differential equation can contain z. We obtain the variational equations for backward stochastic differential equations, and then obtain the maximum principle which solves completely Peng’s open problem.
26 schema:genre research_article
27 schema:inLanguage en
28 schema:isAccessibleForFree true
29 schema:isPartOf Nc6bcdb1c899c4af9ab22f77bd2d26b97
30 Nd2b4856a54d14a268a0cbaa142468f1b
31 sg:journal.1290466
32 schema:name Stochastic global maximum principle for optimization with recursive utilities
33 schema:pagination 1
34 schema:productId N0e0e8ea3ff8f40baa02c3ff4c77379e9
35 N6aaa4b1974d64cb9b90b3338ca271657
36 Ncc6ea8044ab14987b0b9aa2ec56d6f40
37 schema:sameAs https://app.dimensions.ai/details/publication/pub.1083720146
38 https://doi.org/10.1186/s41546-017-0014-7
39 schema:sdDatePublished 2019-04-11T12:27
40 schema:sdLicense https://scigraph.springernature.com/explorer/license/
41 schema:sdPublisher N5c7eb19f437148d4a4bfc13620925eed
42 schema:url https://link.springer.com/10.1186%2Fs41546-017-0014-7
43 sgo:license sg:explorer/license/
44 sgo:sdDataset articles
45 rdf:type schema:ScholarlyArticle
46 N0e0e8ea3ff8f40baa02c3ff4c77379e9 schema:name dimensions_id
47 schema:value pub.1083720146
48 rdf:type schema:PropertyValue
49 N5c7eb19f437148d4a4bfc13620925eed schema:name Springer Nature - SN SciGraph project
50 rdf:type schema:Organization
51 N6aaa4b1974d64cb9b90b3338ca271657 schema:name doi
52 schema:value 10.1186/s41546-017-0014-7
53 rdf:type schema:PropertyValue
54 Nb6ffd362fbb9485b833ce8c7ca2059f7 rdf:first sg:person.014520253357.48
55 rdf:rest rdf:nil
56 Nc6bcdb1c899c4af9ab22f77bd2d26b97 schema:volumeNumber 2
57 rdf:type schema:PublicationVolume
58 Ncc6ea8044ab14987b0b9aa2ec56d6f40 schema:name readcube_id
59 schema:value 26ef6c0999b863a2abdd9103430b3c8150e0491377210c0790c5797b17507b18
60 rdf:type schema:PropertyValue
61 Nd2b4856a54d14a268a0cbaa142468f1b schema:issueNumber 1
62 rdf:type schema:PublicationIssue
63 anzsrc-for:01 schema:inDefinedTermSet anzsrc-for:
64 schema:name Mathematical Sciences
65 rdf:type schema:DefinedTerm
66 anzsrc-for:0102 schema:inDefinedTermSet anzsrc-for:
67 schema:name Applied Mathematics
68 rdf:type schema:DefinedTerm
69 sg:journal.1290466 schema:issn 2367-0126
70 schema:name Probability, Uncertainty and Quantitative Risk
71 rdf:type schema:Periodical
72 sg:person.014520253357.48 schema:affiliation https://www.grid.ac/institutes/grid.27255.37
73 schema:familyName Hu
74 schema:givenName Mingshang
75 schema:sameAs https://app.dimensions.ai/discover/publication?and_facet_researcher=ur.014520253357.48
76 rdf:type schema:Person
77 sg:pub.10.1007/978-0-387-35359-3_32 schema:sameAs https://app.dimensions.ai/details/publication/pub.1030292727
78 https://doi.org/10.1007/978-0-387-35359-3_32
79 rdf:type schema:CreativeWork
80 sg:pub.10.1007/978-1-4612-1466-3 schema:sameAs https://app.dimensions.ai/details/publication/pub.1013764448
81 https://doi.org/10.1007/978-1-4612-1466-3
82 rdf:type schema:CreativeWork
83 sg:pub.10.1007/bf01195978 schema:sameAs https://app.dimensions.ai/details/publication/pub.1035616904
84 https://doi.org/10.1007/bf01195978
85 rdf:type schema:CreativeWork
86 https://app.dimensions.ai/details/publication/pub.1013764448 schema:CreativeWork
87 https://doi.org/10.1006/jmaa.1999.6515 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043700742
88 rdf:type schema:CreativeWork
89 https://doi.org/10.1016/0167-6911(90)90082-6 schema:sameAs https://app.dimensions.ai/details/publication/pub.1048954288
90 rdf:type schema:CreativeWork
91 https://doi.org/10.1016/j.automatica.2013.02.005 schema:sameAs https://app.dimensions.ai/details/publication/pub.1011815320
92 rdf:type schema:CreativeWork
93 https://doi.org/10.1016/s0304-4149(03)00089-9 schema:sameAs https://app.dimensions.ai/details/publication/pub.1022087436
94 rdf:type schema:CreativeWork
95 https://doi.org/10.1017/s0334270000007645 schema:sameAs https://app.dimensions.ai/details/publication/pub.1043240724
96 rdf:type schema:CreativeWork
97 https://doi.org/10.1111/1467-9965.00022 schema:sameAs https://app.dimensions.ai/details/publication/pub.1023508949
98 rdf:type schema:CreativeWork
99 https://doi.org/10.1111/1468-0262.00337 schema:sameAs https://app.dimensions.ai/details/publication/pub.1049495435
100 rdf:type schema:CreativeWork
101 https://doi.org/10.1137/0328054 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062844229
102 rdf:type schema:CreativeWork
103 https://doi.org/10.1137/090763287 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062856460
104 rdf:type schema:CreativeWork
105 https://doi.org/10.1137/s0363012900374737 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062880431
106 rdf:type schema:CreativeWork
107 https://doi.org/10.1137/s0363012992233858 schema:sameAs https://app.dimensions.ai/details/publication/pub.1062880915
108 rdf:type schema:CreativeWork
109 https://doi.org/10.1137/s036301299834973x schema:sameAs https://app.dimensions.ai/details/publication/pub.1062881519
110 rdf:type schema:CreativeWork
111 https://doi.org/10.1214/aoap/1015345345 schema:sameAs https://app.dimensions.ai/details/publication/pub.1064397436
112 rdf:type schema:CreativeWork
113 https://doi.org/10.2307/2951600 schema:sameAs https://app.dimensions.ai/details/publication/pub.1070145901
114 rdf:type schema:CreativeWork
115 https://doi.org/10.4310/cis.2006.v6.n4.a4 schema:sameAs https://app.dimensions.ai/details/publication/pub.1072458441
116 rdf:type schema:CreativeWork
117 https://www.grid.ac/institutes/grid.27255.37 schema:alternateName Shandong University
118 schema:name Zhongtai Institute of Finance, Shandong University, Jinan, 250100, Shandong, People’s Republic of China
119 rdf:type schema:Organization
 




Preview window. Press ESC to close (or click here)


...