Unsynchronized Decentralized Q-Learning: Two Timescale Analysis By Persistence Article Swipe
Bora Yongacoglu
,
Gürdal Arslan
,
Serdar Yüksel
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2308.03239
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.48550/arxiv.2308.03239
Non-stationarity is a fundamental challenge in multi-agent reinforcement learning (MARL), where agents update their behaviour as they learn. Many theoretical advances in MARL avoid the challenge of non-stationarity by coordinating the policy updates of agents in various ways, including synchronizing times at which agents are allowed to revise their policies. Synchronization enables analysis of many MARL algorithms via multi-timescale methods, but such synchronization is infeasible in many decentralized applications. In this paper, we study an unsynchronized variant of the decentralized Q-learning algorithm, a recent MARL algorithm for stochastic games. We provide sufficient conditions under which the unsynchronized algorithm drives play to equilibrium with high probability. Our solution utilizes constant learning rates in the Q-factor update, which we show to be critical for relaxing the synchronization assumptions of earlier work. Our analysis also applies to unsynchronized generalizations of a number of other algorithms from the regret testing tradition, whose performance is analyzed by multi-timescale methods that study Markov chains obtained via policy update dynamics. This work extends the applicability of the decentralized Q-learning algorithm and its relatives to settings in which parameters are selected in an independent manner, and tames non-stationarity without imposing the coordination assumptions of prior work.
Related Topics
Concepts
Asynchronous communication
Regret
Computer science
Synchronizing
Q-learning
Markov chain
Synchronization (alternating current)
Reinforcement learning
Work (physics)
Mathematical optimization
Distributed computing
Theoretical computer science
Artificial intelligence
Machine learning
Mathematics
Engineering
Transmission (telecommunications)
Telecommunications
Computer network
Channel (broadcasting)
Mechanical engineering
Metadata
- Type
- preprint
- Language
- en
- Landing Page
- http://arxiv.org/abs/2308.03239
- https://arxiv.org/pdf/2308.03239
- OA Status
- green
- Cited By
- 1
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4385681682
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4385681682Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.48550/arxiv.2308.03239Digital Object Identifier
- Title
-
Unsynchronized Decentralized Q-Learning: Two Timescale Analysis By PersistenceWork title
- Type
-
preprintOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-08-07Full publication date if available
- Authors
-
Bora Yongacoglu, Gürdal Arslan, Serdar YükselList of authors in order
- Landing page
-
https://arxiv.org/abs/2308.03239Publisher landing page
- PDF URL
-
https://arxiv.org/pdf/2308.03239Direct link to full text PDF
- Open access
-
YesWhether a free full text is available
- OA status
-
greenOpen access status per OpenAlex
- OA URL
-
https://arxiv.org/pdf/2308.03239Direct OA link when available
- Concepts
-
Asynchronous communication, Regret, Computer science, Synchronizing, Q-learning, Markov chain, Synchronization (alternating current), Reinforcement learning, Work (physics), Mathematical optimization, Distributed computing, Theoretical computer science, Artificial intelligence, Machine learning, Mathematics, Engineering, Transmission (telecommunications), Telecommunications, Computer network, Channel (broadcasting), Mechanical engineeringTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2023: 1Per-year citation counts (last 5 years)
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4385681682 |
|---|---|
| doi | https://doi.org/10.48550/arxiv.2308.03239 |
| ids.doi | https://doi.org/10.48550/arxiv.2308.03239 |
| ids.openalex | https://openalex.org/W4385681682 |
| fwci | |
| type | preprint |
| title | Unsynchronized Decentralized Q-Learning: Two Timescale Analysis By Persistence |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | |
| biblio.first_page | |
| topics[0].id | https://openalex.org/T11031 |
| topics[0].field.id | https://openalex.org/fields/18 |
| topics[0].field.display_name | Decision Sciences |
| topics[0].score | 0.9825000166893005 |
| topics[0].domain.id | https://openalex.org/domains/2 |
| topics[0].domain.display_name | Social Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1803 |
| topics[0].subfield.display_name | Management Science and Operations Research |
| topics[0].display_name | Game Theory and Applications |
| topics[1].id | https://openalex.org/T13553 |
| topics[1].field.id | https://openalex.org/fields/17 |
| topics[1].field.display_name | Computer Science |
| topics[1].score | 0.9674000144004822 |
| topics[1].domain.id | https://openalex.org/domains/3 |
| topics[1].domain.display_name | Physical Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/1705 |
| topics[1].subfield.display_name | Computer Networks and Communications |
| topics[1].display_name | Age of Information Optimization |
| topics[2].id | https://openalex.org/T10462 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.958899974822998 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1702 |
| topics[2].subfield.display_name | Artificial Intelligence |
| topics[2].display_name | Reinforcement Learning in Robotics |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C151319957 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8505383729934692 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q752739 |
| concepts[0].display_name | Asynchronous communication |
| concepts[1].id | https://openalex.org/C50817715 |
| concepts[1].level | 2 |
| concepts[1].score | 0.7231011986732483 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q79895177 |
| concepts[1].display_name | Regret |
| concepts[2].id | https://openalex.org/C41008148 |
| concepts[2].level | 0 |
| concepts[2].score | 0.7159298658370972 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[2].display_name | Computer science |
| concepts[3].id | https://openalex.org/C162932704 |
| concepts[3].level | 3 |
| concepts[3].score | 0.7140107154846191 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q1058791 |
| concepts[3].display_name | Synchronizing |
| concepts[4].id | https://openalex.org/C188116033 |
| concepts[4].level | 3 |
| concepts[4].score | 0.6552199125289917 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q2664563 |
| concepts[4].display_name | Q-learning |
| concepts[5].id | https://openalex.org/C98763669 |
| concepts[5].level | 2 |
| concepts[5].score | 0.5992540717124939 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q176645 |
| concepts[5].display_name | Markov chain |
| concepts[6].id | https://openalex.org/C2778562939 |
| concepts[6].level | 3 |
| concepts[6].score | 0.5885441303253174 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q1298791 |
| concepts[6].display_name | Synchronization (alternating current) |
| concepts[7].id | https://openalex.org/C97541855 |
| concepts[7].level | 2 |
| concepts[7].score | 0.5476599335670471 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q830687 |
| concepts[7].display_name | Reinforcement learning |
| concepts[8].id | https://openalex.org/C18762648 |
| concepts[8].level | 2 |
| concepts[8].score | 0.41030603647232056 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q42213 |
| concepts[8].display_name | Work (physics) |
| concepts[9].id | https://openalex.org/C126255220 |
| concepts[9].level | 1 |
| concepts[9].score | 0.3718389570713043 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q141495 |
| concepts[9].display_name | Mathematical optimization |
| concepts[10].id | https://openalex.org/C120314980 |
| concepts[10].level | 1 |
| concepts[10].score | 0.3437376618385315 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q180634 |
| concepts[10].display_name | Distributed computing |
| concepts[11].id | https://openalex.org/C80444323 |
| concepts[11].level | 1 |
| concepts[11].score | 0.32344645261764526 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q2878974 |
| concepts[11].display_name | Theoretical computer science |
| concepts[12].id | https://openalex.org/C154945302 |
| concepts[12].level | 1 |
| concepts[12].score | 0.21949347853660583 |
| concepts[12].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[12].display_name | Artificial intelligence |
| concepts[13].id | https://openalex.org/C119857082 |
| concepts[13].level | 1 |
| concepts[13].score | 0.20381119847297668 |
| concepts[13].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[13].display_name | Machine learning |
| concepts[14].id | https://openalex.org/C33923547 |
| concepts[14].level | 0 |
| concepts[14].score | 0.18284037709236145 |
| concepts[14].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[14].display_name | Mathematics |
| concepts[15].id | https://openalex.org/C127413603 |
| concepts[15].level | 0 |
| concepts[15].score | 0.07869976758956909 |
| concepts[15].wikidata | https://www.wikidata.org/wiki/Q11023 |
| concepts[15].display_name | Engineering |
| concepts[16].id | https://openalex.org/C761482 |
| concepts[16].level | 2 |
| concepts[16].score | 0.0 |
| concepts[16].wikidata | https://www.wikidata.org/wiki/Q118093 |
| concepts[16].display_name | Transmission (telecommunications) |
| concepts[17].id | https://openalex.org/C76155785 |
| concepts[17].level | 1 |
| concepts[17].score | 0.0 |
| concepts[17].wikidata | https://www.wikidata.org/wiki/Q418 |
| concepts[17].display_name | Telecommunications |
| concepts[18].id | https://openalex.org/C31258907 |
| concepts[18].level | 1 |
| concepts[18].score | 0.0 |
| concepts[18].wikidata | https://www.wikidata.org/wiki/Q1301371 |
| concepts[18].display_name | Computer network |
| concepts[19].id | https://openalex.org/C127162648 |
| concepts[19].level | 2 |
| concepts[19].score | 0.0 |
| concepts[19].wikidata | https://www.wikidata.org/wiki/Q16858953 |
| concepts[19].display_name | Channel (broadcasting) |
| concepts[20].id | https://openalex.org/C78519656 |
| concepts[20].level | 1 |
| concepts[20].score | 0.0 |
| concepts[20].wikidata | https://www.wikidata.org/wiki/Q101333 |
| concepts[20].display_name | Mechanical engineering |
| keywords[0].id | https://openalex.org/keywords/asynchronous-communication |
| keywords[0].score | 0.8505383729934692 |
| keywords[0].display_name | Asynchronous communication |
| keywords[1].id | https://openalex.org/keywords/regret |
| keywords[1].score | 0.7231011986732483 |
| keywords[1].display_name | Regret |
| keywords[2].id | https://openalex.org/keywords/computer-science |
| keywords[2].score | 0.7159298658370972 |
| keywords[2].display_name | Computer science |
| keywords[3].id | https://openalex.org/keywords/synchronizing |
| keywords[3].score | 0.7140107154846191 |
| keywords[3].display_name | Synchronizing |
| keywords[4].id | https://openalex.org/keywords/q-learning |
| keywords[4].score | 0.6552199125289917 |
| keywords[4].display_name | Q-learning |
| keywords[5].id | https://openalex.org/keywords/markov-chain |
| keywords[5].score | 0.5992540717124939 |
| keywords[5].display_name | Markov chain |
| keywords[6].id | https://openalex.org/keywords/synchronization |
| keywords[6].score | 0.5885441303253174 |
| keywords[6].display_name | Synchronization (alternating current) |
| keywords[7].id | https://openalex.org/keywords/reinforcement-learning |
| keywords[7].score | 0.5476599335670471 |
| keywords[7].display_name | Reinforcement learning |
| keywords[8].id | https://openalex.org/keywords/work |
| keywords[8].score | 0.41030603647232056 |
| keywords[8].display_name | Work (physics) |
| keywords[9].id | https://openalex.org/keywords/mathematical-optimization |
| keywords[9].score | 0.3718389570713043 |
| keywords[9].display_name | Mathematical optimization |
| keywords[10].id | https://openalex.org/keywords/distributed-computing |
| keywords[10].score | 0.3437376618385315 |
| keywords[10].display_name | Distributed computing |
| keywords[11].id | https://openalex.org/keywords/theoretical-computer-science |
| keywords[11].score | 0.32344645261764526 |
| keywords[11].display_name | Theoretical computer science |
| keywords[12].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[12].score | 0.21949347853660583 |
| keywords[12].display_name | Artificial intelligence |
| keywords[13].id | https://openalex.org/keywords/machine-learning |
| keywords[13].score | 0.20381119847297668 |
| keywords[13].display_name | Machine learning |
| keywords[14].id | https://openalex.org/keywords/mathematics |
| keywords[14].score | 0.18284037709236145 |
| keywords[14].display_name | Mathematics |
| keywords[15].id | https://openalex.org/keywords/engineering |
| keywords[15].score | 0.07869976758956909 |
| keywords[15].display_name | Engineering |
| language | en |
| locations[0].id | pmh:oai:arXiv.org:2308.03239 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4306400194 |
| locations[0].source.issn | |
| locations[0].source.type | repository |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | arXiv (Cornell University) |
| locations[0].source.host_organization | https://openalex.org/I205783295 |
| locations[0].source.host_organization_name | Cornell University |
| locations[0].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[0].license | |
| locations[0].pdf_url | https://arxiv.org/pdf/2308.03239 |
| locations[0].version | submittedVersion |
| locations[0].raw_type | text |
| locations[0].license_id | |
| locations[0].is_accepted | False |
| locations[0].is_published | False |
| locations[0].raw_source_name | |
| locations[0].landing_page_url | http://arxiv.org/abs/2308.03239 |
| locations[1].id | doi:10.48550/arxiv.2308.03239 |
| locations[1].is_oa | True |
| locations[1].source.id | https://openalex.org/S4306400194 |
| locations[1].source.issn | |
| locations[1].source.type | repository |
| locations[1].source.is_oa | True |
| locations[1].source.issn_l | |
| locations[1].source.is_core | False |
| locations[1].source.is_in_doaj | False |
| locations[1].source.display_name | arXiv (Cornell University) |
| locations[1].source.host_organization | https://openalex.org/I205783295 |
| locations[1].source.host_organization_name | Cornell University |
| locations[1].source.host_organization_lineage | https://openalex.org/I205783295 |
| locations[1].license | cc-by |
| locations[1].pdf_url | |
| locations[1].version | |
| locations[1].raw_type | article |
| locations[1].license_id | https://openalex.org/licenses/cc-by |
| locations[1].is_accepted | False |
| locations[1].is_published | |
| locations[1].raw_source_name | |
| locations[1].landing_page_url | https://doi.org/10.48550/arxiv.2308.03239 |
| indexed_in | arxiv, datacite |
| authorships[0].author.id | https://openalex.org/A5017866507 |
| authorships[0].author.orcid | |
| authorships[0].author.display_name | Bora Yongacoglu |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | Yongacoglu, Bora |
| authorships[0].is_corresponding | False |
| authorships[1].author.id | https://openalex.org/A5072860374 |
| authorships[1].author.orcid | https://orcid.org/0000-0002-8295-1509 |
| authorships[1].author.display_name | Gürdal Arslan |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | Arslan, Gürdal |
| authorships[1].is_corresponding | False |
| authorships[2].author.id | https://openalex.org/A5005401257 |
| authorships[2].author.orcid | https://orcid.org/0000-0001-6099-5001 |
| authorships[2].author.display_name | Serdar Yüksel |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | Yüksel, Serdar |
| authorships[2].is_corresponding | False |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://arxiv.org/pdf/2308.03239 |
| open_access.oa_status | green |
| open_access.any_repository_has_fulltext | False |
| created_date | 2023-08-09T00:00:00 |
| display_name | Unsynchronized Decentralized Q-Learning: Two Timescale Analysis By Persistence |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T06:51:31.235846 |
| primary_topic.id | https://openalex.org/T11031 |
| primary_topic.field.id | https://openalex.org/fields/18 |
| primary_topic.field.display_name | Decision Sciences |
| primary_topic.score | 0.9825000166893005 |
| primary_topic.domain.id | https://openalex.org/domains/2 |
| primary_topic.domain.display_name | Social Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1803 |
| primary_topic.subfield.display_name | Management Science and Operations Research |
| primary_topic.display_name | Game Theory and Applications |
| related_works | https://openalex.org/W4292701710, https://openalex.org/W2141223633, https://openalex.org/W96967322, https://openalex.org/W2147711412, https://openalex.org/W3096874164, https://openalex.org/W2166117066, https://openalex.org/W2357975469, https://openalex.org/W2970347269, https://openalex.org/W2136202932, https://openalex.org/W3087814763 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2023 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 2 |
| best_oa_location.id | pmh:oai:arXiv.org:2308.03239 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4306400194 |
| best_oa_location.source.issn | |
| best_oa_location.source.type | repository |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | arXiv (Cornell University) |
| best_oa_location.source.host_organization | https://openalex.org/I205783295 |
| best_oa_location.source.host_organization_name | Cornell University |
| best_oa_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| best_oa_location.license | |
| best_oa_location.pdf_url | https://arxiv.org/pdf/2308.03239 |
| best_oa_location.version | submittedVersion |
| best_oa_location.raw_type | text |
| best_oa_location.license_id | |
| best_oa_location.is_accepted | False |
| best_oa_location.is_published | False |
| best_oa_location.raw_source_name | |
| best_oa_location.landing_page_url | http://arxiv.org/abs/2308.03239 |
| primary_location.id | pmh:oai:arXiv.org:2308.03239 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4306400194 |
| primary_location.source.issn | |
| primary_location.source.type | repository |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | arXiv (Cornell University) |
| primary_location.source.host_organization | https://openalex.org/I205783295 |
| primary_location.source.host_organization_name | Cornell University |
| primary_location.source.host_organization_lineage | https://openalex.org/I205783295 |
| primary_location.license | |
| primary_location.pdf_url | https://arxiv.org/pdf/2308.03239 |
| primary_location.version | submittedVersion |
| primary_location.raw_type | text |
| primary_location.license_id | |
| primary_location.is_accepted | False |
| primary_location.is_published | False |
| primary_location.raw_source_name | |
| primary_location.landing_page_url | http://arxiv.org/abs/2308.03239 |
| publication_date | 2023-08-07 |
| publication_year | 2023 |
| referenced_works_count | 0 |
| abstract_inverted_index.a | 2, 82, 137 |
| abstract_inverted_index.In | 69 |
| abstract_inverted_index.We | 89 |
| abstract_inverted_index.an | 74, 184 |
| abstract_inverted_index.as | 15 |
| abstract_inverted_index.at | 41 |
| abstract_inverted_index.be | 119 |
| abstract_inverted_index.by | 28, 151 |
| abstract_inverted_index.in | 5, 21, 35, 65, 111, 178, 183 |
| abstract_inverted_index.is | 1, 63, 149 |
| abstract_inverted_index.of | 26, 33, 53, 77, 126, 136, 139, 168, 195 |
| abstract_inverted_index.to | 46, 100, 118, 133, 176 |
| abstract_inverted_index.we | 72, 116 |
| abstract_inverted_index.Our | 105, 129 |
| abstract_inverted_index.and | 173, 187 |
| abstract_inverted_index.are | 44, 181 |
| abstract_inverted_index.but | 60 |
| abstract_inverted_index.for | 86, 121 |
| abstract_inverted_index.its | 174 |
| abstract_inverted_index.the | 24, 30, 78, 95, 112, 123, 143, 166, 169, 192 |
| abstract_inverted_index.via | 57, 159 |
| abstract_inverted_index.MARL | 22, 55, 84 |
| abstract_inverted_index.Many | 18 |
| abstract_inverted_index.This | 163 |
| abstract_inverted_index.also | 131 |
| abstract_inverted_index.from | 142 |
| abstract_inverted_index.high | 103 |
| abstract_inverted_index.many | 54, 66 |
| abstract_inverted_index.play | 99 |
| abstract_inverted_index.show | 117 |
| abstract_inverted_index.such | 61 |
| abstract_inverted_index.that | 154 |
| abstract_inverted_index.they | 16 |
| abstract_inverted_index.this | 70 |
| abstract_inverted_index.with | 102 |
| abstract_inverted_index.work | 164 |
| abstract_inverted_index.avoid | 23 |
| abstract_inverted_index.other | 140 |
| abstract_inverted_index.prior | 196 |
| abstract_inverted_index.rates | 110 |
| abstract_inverted_index.study | 73, 155 |
| abstract_inverted_index.tames | 188 |
| abstract_inverted_index.their | 13, 48 |
| abstract_inverted_index.times | 40 |
| abstract_inverted_index.under | 93 |
| abstract_inverted_index.ways, | 37 |
| abstract_inverted_index.where | 10 |
| abstract_inverted_index.which | 42, 94, 115, 179 |
| abstract_inverted_index.whose | 147 |
| abstract_inverted_index.work. | 128, 197 |
| abstract_inverted_index.Markov | 156 |
| abstract_inverted_index.agents | 11, 34, 43 |
| abstract_inverted_index.chains | 157 |
| abstract_inverted_index.drives | 98 |
| abstract_inverted_index.games. | 88 |
| abstract_inverted_index.learn. | 17 |
| abstract_inverted_index.number | 138 |
| abstract_inverted_index.paper, | 71 |
| abstract_inverted_index.policy | 31, 160 |
| abstract_inverted_index.recent | 83 |
| abstract_inverted_index.regret | 144 |
| abstract_inverted_index.revise | 47 |
| abstract_inverted_index.update | 12, 161 |
| abstract_inverted_index.(MARL), | 9 |
| abstract_inverted_index.allowed | 45 |
| abstract_inverted_index.applies | 132 |
| abstract_inverted_index.earlier | 127 |
| abstract_inverted_index.enables | 51 |
| abstract_inverted_index.extends | 165 |
| abstract_inverted_index.manner, | 186 |
| abstract_inverted_index.methods | 153 |
| abstract_inverted_index.provide | 90 |
| abstract_inverted_index.testing | 145 |
| abstract_inverted_index.update, | 114 |
| abstract_inverted_index.updates | 32 |
| abstract_inverted_index.variant | 76 |
| abstract_inverted_index.various | 36 |
| abstract_inverted_index.without | 190 |
| abstract_inverted_index.Q-factor | 113 |
| abstract_inverted_index.advances | 20 |
| abstract_inverted_index.analysis | 52, 130 |
| abstract_inverted_index.analyzed | 150 |
| abstract_inverted_index.constant | 108 |
| abstract_inverted_index.critical | 120 |
| abstract_inverted_index.imposing | 191 |
| abstract_inverted_index.learning | 8, 109 |
| abstract_inverted_index.methods, | 59 |
| abstract_inverted_index.obtained | 158 |
| abstract_inverted_index.relaxing | 122 |
| abstract_inverted_index.selected | 182 |
| abstract_inverted_index.settings | 177 |
| abstract_inverted_index.solution | 106 |
| abstract_inverted_index.utilizes | 107 |
| abstract_inverted_index.algorithm | 85, 97, 172 |
| abstract_inverted_index.behaviour | 14 |
| abstract_inverted_index.challenge | 4, 25 |
| abstract_inverted_index.dynamics. | 162 |
| abstract_inverted_index.including | 38 |
| abstract_inverted_index.policies. | 49 |
| abstract_inverted_index.relatives | 175 |
| abstract_inverted_index.Q-learning | 80, 171 |
| abstract_inverted_index.algorithm, | 81 |
| abstract_inverted_index.algorithms | 56, 141 |
| abstract_inverted_index.conditions | 92 |
| abstract_inverted_index.infeasible | 64 |
| abstract_inverted_index.parameters | 180 |
| abstract_inverted_index.stochastic | 87 |
| abstract_inverted_index.sufficient | 91 |
| abstract_inverted_index.tradition, | 146 |
| abstract_inverted_index.assumptions | 125, 194 |
| abstract_inverted_index.equilibrium | 101 |
| abstract_inverted_index.fundamental | 3 |
| abstract_inverted_index.independent | 185 |
| abstract_inverted_index.multi-agent | 6 |
| abstract_inverted_index.performance | 148 |
| abstract_inverted_index.theoretical | 19 |
| abstract_inverted_index.coordinating | 29 |
| abstract_inverted_index.coordination | 193 |
| abstract_inverted_index.probability. | 104 |
| abstract_inverted_index.applicability | 167 |
| abstract_inverted_index.applications. | 68 |
| abstract_inverted_index.decentralized | 67, 79, 170 |
| abstract_inverted_index.reinforcement | 7 |
| abstract_inverted_index.synchronizing | 39 |
| abstract_inverted_index.unsynchronized | 75, 96, 134 |
| abstract_inverted_index.Synchronization | 50 |
| abstract_inverted_index.generalizations | 135 |
| abstract_inverted_index.multi-timescale | 58, 152 |
| abstract_inverted_index.synchronization | 62, 124 |
| abstract_inverted_index.Non-stationarity | 0 |
| abstract_inverted_index.non-stationarity | 27, 189 |
| cited_by_percentile_year | |
| countries_distinct_count | 0 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.6200000047683716 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile |