Introduction of Reinforcement Learning and Its Application Across Different Domain Article Swipe
Harshita Sharma
,
Hritik Kumar
,
Rashmi Pandey
·
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.32628/cseit239066
YOU?
·
· 2023
· Open Access
·
· DOI: https://doi.org/10.32628/cseit239066
In the modern era of rapid development in Deep Neural Networks, Reinforcement Learning (RL) has evolved into a pivotal and transformative technology. RL, a learning process where these machine agent interacts with several unknown environment through trial and error. The agent, responsive to the learning machine, go through these interaction, and start receiving feedback in the form of positive rewards or negative rewards like penalties from the environment, and constantly refines its behavior. This research paper offers an in-depth introduction to the foundational concepts of RL, focusing on Markov Decision Processes and various RL algorithms. Machine Learning (ML) is a subset of Artificial Intelligence, which deals with ‘‘the question of how to develop software agents (Machine) that improve automatically with experience’’. The basic three categories of Machine Learning are. Supervised Learning Unsupervised Learning Reinforcement Learning RL method is that in any situation the agent has to choose between using its acquired knowledge of the environment i.e. using an action already tried or performed previously or exploring actions never tried before in that situation. In this review paper, we will discuss the most used learning algorithms in games robotics and healthcare, autonomous control as well as communication and networking, natural language processing.[1]
Related Topics
Concepts
Metadata
- Type
- article
- Language
- en
- Landing Page
- https://doi.org/10.32628/cseit239066
- OA Status
- diamond
- Cited By
- 1
- References
- 6
- Related Works
- 10
- OpenAlex ID
- https://openalex.org/W4390678581
All OpenAlex metadata
Raw OpenAlex JSON
- OpenAlex ID
-
https://openalex.org/W4390678581Canonical identifier for this work in OpenAlex
- DOI
-
https://doi.org/10.32628/cseit239066Digital Object Identifier
- Title
-
Introduction of Reinforcement Learning and Its Application Across Different DomainWork title
- Type
-
articleOpenAlex work type
- Language
-
enPrimary language
- Publication year
-
2023Year of publication
- Publication date
-
2023-11-05Full publication date if available
- Authors
-
Harshita Sharma, Hritik Kumar, Rashmi PandeyList of authors in order
- Landing page
-
https://doi.org/10.32628/cseit239066Publisher landing page
- Open access
-
YesWhether a free full text is available
- OA status
-
diamondOpen access status per OpenAlex
- OA URL
-
https://doi.org/10.32628/cseit239066Direct OA link when available
- Concepts
-
Reinforcement learning, Artificial intelligence, Machine learning, Computer science, Transformative learning, Markov decision process, Control (management), Psychology, Markov process, Mathematics, Pedagogy, StatisticsTop concepts (fields/topics) attached by OpenAlex
- Cited by
-
1Total citation count in OpenAlex
- Citations by year (recent)
-
2025: 1Per-year citation counts (last 5 years)
- References (count)
-
6Number of works referenced by this work
- Related works (count)
-
10Other works algorithmically related by OpenAlex
Full payload
| id | https://openalex.org/W4390678581 |
|---|---|
| doi | https://doi.org/10.32628/cseit239066 |
| ids.doi | https://doi.org/10.32628/cseit239066 |
| ids.openalex | https://openalex.org/W4390678581 |
| fwci | 0.25544289 |
| type | article |
| title | Introduction of Reinforcement Learning and Its Application Across Different Domain |
| biblio.issue | |
| biblio.volume | |
| biblio.last_page | 104 |
| biblio.first_page | 98 |
| topics[0].id | https://openalex.org/T12761 |
| topics[0].field.id | https://openalex.org/fields/17 |
| topics[0].field.display_name | Computer Science |
| topics[0].score | 0.9797999858856201 |
| topics[0].domain.id | https://openalex.org/domains/3 |
| topics[0].domain.display_name | Physical Sciences |
| topics[0].subfield.id | https://openalex.org/subfields/1702 |
| topics[0].subfield.display_name | Artificial Intelligence |
| topics[0].display_name | Data Stream Mining Techniques |
| topics[1].id | https://openalex.org/T10429 |
| topics[1].field.id | https://openalex.org/fields/28 |
| topics[1].field.display_name | Neuroscience |
| topics[1].score | 0.939300000667572 |
| topics[1].domain.id | https://openalex.org/domains/1 |
| topics[1].domain.display_name | Life Sciences |
| topics[1].subfield.id | https://openalex.org/subfields/2805 |
| topics[1].subfield.display_name | Cognitive Neuroscience |
| topics[1].display_name | EEG and Brain-Computer Interfaces |
| topics[2].id | https://openalex.org/T10270 |
| topics[2].field.id | https://openalex.org/fields/17 |
| topics[2].field.display_name | Computer Science |
| topics[2].score | 0.9143999814987183 |
| topics[2].domain.id | https://openalex.org/domains/3 |
| topics[2].domain.display_name | Physical Sciences |
| topics[2].subfield.id | https://openalex.org/subfields/1710 |
| topics[2].subfield.display_name | Information Systems |
| topics[2].display_name | Blockchain Technology Applications and Security |
| is_xpac | False |
| apc_list | |
| apc_paid | |
| concepts[0].id | https://openalex.org/C97541855 |
| concepts[0].level | 2 |
| concepts[0].score | 0.8022122979164124 |
| concepts[0].wikidata | https://www.wikidata.org/wiki/Q830687 |
| concepts[0].display_name | Reinforcement learning |
| concepts[1].id | https://openalex.org/C154945302 |
| concepts[1].level | 1 |
| concepts[1].score | 0.7593127489089966 |
| concepts[1].wikidata | https://www.wikidata.org/wiki/Q11660 |
| concepts[1].display_name | Artificial intelligence |
| concepts[2].id | https://openalex.org/C119857082 |
| concepts[2].level | 1 |
| concepts[2].score | 0.5933398604393005 |
| concepts[2].wikidata | https://www.wikidata.org/wiki/Q2539 |
| concepts[2].display_name | Machine learning |
| concepts[3].id | https://openalex.org/C41008148 |
| concepts[3].level | 0 |
| concepts[3].score | 0.5791379809379578 |
| concepts[3].wikidata | https://www.wikidata.org/wiki/Q21198 |
| concepts[3].display_name | Computer science |
| concepts[4].id | https://openalex.org/C70587473 |
| concepts[4].level | 2 |
| concepts[4].score | 0.5703086853027344 |
| concepts[4].wikidata | https://www.wikidata.org/wiki/Q7834111 |
| concepts[4].display_name | Transformative learning |
| concepts[5].id | https://openalex.org/C106189395 |
| concepts[5].level | 3 |
| concepts[5].score | 0.47538769245147705 |
| concepts[5].wikidata | https://www.wikidata.org/wiki/Q176789 |
| concepts[5].display_name | Markov decision process |
| concepts[6].id | https://openalex.org/C2775924081 |
| concepts[6].level | 2 |
| concepts[6].score | 0.41657692193984985 |
| concepts[6].wikidata | https://www.wikidata.org/wiki/Q55608371 |
| concepts[6].display_name | Control (management) |
| concepts[7].id | https://openalex.org/C15744967 |
| concepts[7].level | 0 |
| concepts[7].score | 0.2221027910709381 |
| concepts[7].wikidata | https://www.wikidata.org/wiki/Q9418 |
| concepts[7].display_name | Psychology |
| concepts[8].id | https://openalex.org/C159886148 |
| concepts[8].level | 2 |
| concepts[8].score | 0.14062699675559998 |
| concepts[8].wikidata | https://www.wikidata.org/wiki/Q176645 |
| concepts[8].display_name | Markov process |
| concepts[9].id | https://openalex.org/C33923547 |
| concepts[9].level | 0 |
| concepts[9].score | 0.1298120617866516 |
| concepts[9].wikidata | https://www.wikidata.org/wiki/Q395 |
| concepts[9].display_name | Mathematics |
| concepts[10].id | https://openalex.org/C19417346 |
| concepts[10].level | 1 |
| concepts[10].score | 0.0 |
| concepts[10].wikidata | https://www.wikidata.org/wiki/Q7922 |
| concepts[10].display_name | Pedagogy |
| concepts[11].id | https://openalex.org/C105795698 |
| concepts[11].level | 1 |
| concepts[11].score | 0.0 |
| concepts[11].wikidata | https://www.wikidata.org/wiki/Q12483 |
| concepts[11].display_name | Statistics |
| keywords[0].id | https://openalex.org/keywords/reinforcement-learning |
| keywords[0].score | 0.8022122979164124 |
| keywords[0].display_name | Reinforcement learning |
| keywords[1].id | https://openalex.org/keywords/artificial-intelligence |
| keywords[1].score | 0.7593127489089966 |
| keywords[1].display_name | Artificial intelligence |
| keywords[2].id | https://openalex.org/keywords/machine-learning |
| keywords[2].score | 0.5933398604393005 |
| keywords[2].display_name | Machine learning |
| keywords[3].id | https://openalex.org/keywords/computer-science |
| keywords[3].score | 0.5791379809379578 |
| keywords[3].display_name | Computer science |
| keywords[4].id | https://openalex.org/keywords/transformative-learning |
| keywords[4].score | 0.5703086853027344 |
| keywords[4].display_name | Transformative learning |
| keywords[5].id | https://openalex.org/keywords/markov-decision-process |
| keywords[5].score | 0.47538769245147705 |
| keywords[5].display_name | Markov decision process |
| keywords[6].id | https://openalex.org/keywords/control |
| keywords[6].score | 0.41657692193984985 |
| keywords[6].display_name | Control (management) |
| keywords[7].id | https://openalex.org/keywords/psychology |
| keywords[7].score | 0.2221027910709381 |
| keywords[7].display_name | Psychology |
| keywords[8].id | https://openalex.org/keywords/markov-process |
| keywords[8].score | 0.14062699675559998 |
| keywords[8].display_name | Markov process |
| keywords[9].id | https://openalex.org/keywords/mathematics |
| keywords[9].score | 0.1298120617866516 |
| keywords[9].display_name | Mathematics |
| language | en |
| locations[0].id | doi:10.32628/cseit239066 |
| locations[0].is_oa | True |
| locations[0].source.id | https://openalex.org/S4210200847 |
| locations[0].source.issn | 2456-3307 |
| locations[0].source.type | journal |
| locations[0].source.is_oa | True |
| locations[0].source.issn_l | 2456-3307 |
| locations[0].source.is_core | False |
| locations[0].source.is_in_doaj | False |
| locations[0].source.display_name | International Journal of Scientific Research in Computer Science Engineering and Information Technology |
| locations[0].source.host_organization | |
| locations[0].source.host_organization_name | |
| locations[0].license | cc-by |
| locations[0].pdf_url | |
| locations[0].version | publishedVersion |
| locations[0].raw_type | journal-article |
| locations[0].license_id | https://openalex.org/licenses/cc-by |
| locations[0].is_accepted | True |
| locations[0].is_published | True |
| locations[0].raw_source_name | International Journal of Scientific Research in Computer Science, Engineering and Information Technology |
| locations[0].landing_page_url | https://doi.org/10.32628/cseit239066 |
| indexed_in | crossref |
| authorships[0].author.id | https://openalex.org/A5056301773 |
| authorships[0].author.orcid | https://orcid.org/0000-0003-4683-2606 |
| authorships[0].author.display_name | Harshita Sharma |
| authorships[0].countries | IN |
| authorships[0].affiliations[0].institution_ids | https://openalex.org/I9747756 |
| authorships[0].affiliations[0].raw_affiliation_string | Institute of Technology and Management, Gwalior, Madhya Pradesh, India |
| authorships[0].institutions[0].id | https://openalex.org/I9747756 |
| authorships[0].institutions[0].ror | https://ror.org/008b3ap06 |
| authorships[0].institutions[0].type | education |
| authorships[0].institutions[0].lineage | https://openalex.org/I9747756 |
| authorships[0].institutions[0].country_code | IN |
| authorships[0].institutions[0].display_name | Atal Bihari Vajpayee Indian Institute of Information Technology and Management |
| authorships[0].author_position | first |
| authorships[0].raw_author_name | None Harshita Sharma |
| authorships[0].is_corresponding | False |
| authorships[0].raw_affiliation_strings | Institute of Technology and Management, Gwalior, Madhya Pradesh, India |
| authorships[1].author.id | https://openalex.org/A5089677424 |
| authorships[1].author.orcid | https://orcid.org/0009-0009-4131-0914 |
| authorships[1].author.display_name | Hritik Kumar |
| authorships[1].countries | IN |
| authorships[1].affiliations[0].institution_ids | https://openalex.org/I9747756 |
| authorships[1].affiliations[0].raw_affiliation_string | Institute of Technology and Management, Gwalior, Madhya Pradesh, India |
| authorships[1].institutions[0].id | https://openalex.org/I9747756 |
| authorships[1].institutions[0].ror | https://ror.org/008b3ap06 |
| authorships[1].institutions[0].type | education |
| authorships[1].institutions[0].lineage | https://openalex.org/I9747756 |
| authorships[1].institutions[0].country_code | IN |
| authorships[1].institutions[0].display_name | Atal Bihari Vajpayee Indian Institute of Information Technology and Management |
| authorships[1].author_position | middle |
| authorships[1].raw_author_name | None Hritik Kumar |
| authorships[1].is_corresponding | False |
| authorships[1].raw_affiliation_strings | Institute of Technology and Management, Gwalior, Madhya Pradesh, India |
| authorships[2].author.id | https://openalex.org/A5001078952 |
| authorships[2].author.orcid | https://orcid.org/0000-0003-0215-4030 |
| authorships[2].author.display_name | Rashmi Pandey |
| authorships[2].countries | IN |
| authorships[2].affiliations[0].institution_ids | https://openalex.org/I9747756 |
| authorships[2].affiliations[0].raw_affiliation_string | Assistant Professor, Institute of Technology and Management, Gwalior, Madhya Pradesh, India |
| authorships[2].institutions[0].id | https://openalex.org/I9747756 |
| authorships[2].institutions[0].ror | https://ror.org/008b3ap06 |
| authorships[2].institutions[0].type | education |
| authorships[2].institutions[0].lineage | https://openalex.org/I9747756 |
| authorships[2].institutions[0].country_code | IN |
| authorships[2].institutions[0].display_name | Atal Bihari Vajpayee Indian Institute of Information Technology and Management |
| authorships[2].author_position | last |
| authorships[2].raw_author_name | None Rashmi Pandey |
| authorships[2].is_corresponding | False |
| authorships[2].raw_affiliation_strings | Assistant Professor, Institute of Technology and Management, Gwalior, Madhya Pradesh, India |
| has_content.pdf | False |
| has_content.grobid_xml | False |
| is_paratext | False |
| open_access.is_oa | True |
| open_access.oa_url | https://doi.org/10.32628/cseit239066 |
| open_access.oa_status | diamond |
| open_access.any_repository_has_fulltext | False |
| created_date | 2025-10-10T00:00:00 |
| display_name | Introduction of Reinforcement Learning and Its Application Across Different Domain |
| has_fulltext | False |
| is_retracted | False |
| updated_date | 2025-11-06T03:46:38.306776 |
| primary_topic.id | https://openalex.org/T12761 |
| primary_topic.field.id | https://openalex.org/fields/17 |
| primary_topic.field.display_name | Computer Science |
| primary_topic.score | 0.9797999858856201 |
| primary_topic.domain.id | https://openalex.org/domains/3 |
| primary_topic.domain.display_name | Physical Sciences |
| primary_topic.subfield.id | https://openalex.org/subfields/1702 |
| primary_topic.subfield.display_name | Artificial Intelligence |
| primary_topic.display_name | Data Stream Mining Techniques |
| related_works | https://openalex.org/W3096874164, https://openalex.org/W2937181779, https://openalex.org/W2386410636, https://openalex.org/W1985560493, https://openalex.org/W2357975469, https://openalex.org/W2145363145, https://openalex.org/W1626977535, https://openalex.org/W4284974072, https://openalex.org/W2341346307, https://openalex.org/W4225269853 |
| cited_by_count | 1 |
| counts_by_year[0].year | 2025 |
| counts_by_year[0].cited_by_count | 1 |
| locations_count | 1 |
| best_oa_location.id | doi:10.32628/cseit239066 |
| best_oa_location.is_oa | True |
| best_oa_location.source.id | https://openalex.org/S4210200847 |
| best_oa_location.source.issn | 2456-3307 |
| best_oa_location.source.type | journal |
| best_oa_location.source.is_oa | True |
| best_oa_location.source.issn_l | 2456-3307 |
| best_oa_location.source.is_core | False |
| best_oa_location.source.is_in_doaj | False |
| best_oa_location.source.display_name | International Journal of Scientific Research in Computer Science Engineering and Information Technology |
| best_oa_location.source.host_organization | |
| best_oa_location.source.host_organization_name | |
| best_oa_location.license | cc-by |
| best_oa_location.pdf_url | |
| best_oa_location.version | publishedVersion |
| best_oa_location.raw_type | journal-article |
| best_oa_location.license_id | https://openalex.org/licenses/cc-by |
| best_oa_location.is_accepted | True |
| best_oa_location.is_published | True |
| best_oa_location.raw_source_name | International Journal of Scientific Research in Computer Science, Engineering and Information Technology |
| best_oa_location.landing_page_url | https://doi.org/10.32628/cseit239066 |
| primary_location.id | doi:10.32628/cseit239066 |
| primary_location.is_oa | True |
| primary_location.source.id | https://openalex.org/S4210200847 |
| primary_location.source.issn | 2456-3307 |
| primary_location.source.type | journal |
| primary_location.source.is_oa | True |
| primary_location.source.issn_l | 2456-3307 |
| primary_location.source.is_core | False |
| primary_location.source.is_in_doaj | False |
| primary_location.source.display_name | International Journal of Scientific Research in Computer Science Engineering and Information Technology |
| primary_location.source.host_organization | |
| primary_location.source.host_organization_name | |
| primary_location.license | cc-by |
| primary_location.pdf_url | |
| primary_location.version | publishedVersion |
| primary_location.raw_type | journal-article |
| primary_location.license_id | https://openalex.org/licenses/cc-by |
| primary_location.is_accepted | True |
| primary_location.is_published | True |
| primary_location.raw_source_name | International Journal of Scientific Research in Computer Science, Engineering and Information Technology |
| primary_location.landing_page_url | https://doi.org/10.32628/cseit239066 |
| publication_date | 2023-11-05 |
| publication_year | 2023 |
| referenced_works | https://openalex.org/W3099098707, https://openalex.org/W2914656440, https://openalex.org/W4214717370, https://openalex.org/W2619989803, https://openalex.org/W2161336914, https://openalex.org/W2179488730 |
| referenced_works_count | 6 |
| abstract_inverted_index.a | 17, 23, 99 |
| abstract_inverted_index.In | 0 |
| abstract_inverted_index.RL | 93 |
| abstract_inverted_index.an | 77, 159 |
| abstract_inverted_index.as | 194, 196 |
| abstract_inverted_index.go | 46 |
| abstract_inverted_index.in | 7, 54, 141, 172, 187 |
| abstract_inverted_index.is | 98, 139 |
| abstract_inverted_index.of | 4, 57, 84, 101, 109, 125, 154 |
| abstract_inverted_index.on | 87 |
| abstract_inverted_index.or | 60, 163, 166 |
| abstract_inverted_index.to | 42, 80, 111, 147 |
| abstract_inverted_index.we | 179 |
| abstract_inverted_index.RL, | 22, 85 |
| abstract_inverted_index.The | 39, 121 |
| abstract_inverted_index.and | 19, 37, 50, 68, 91, 190, 198 |
| abstract_inverted_index.any | 142 |
| abstract_inverted_index.era | 3 |
| abstract_inverted_index.has | 14, 146 |
| abstract_inverted_index.how | 110 |
| abstract_inverted_index.its | 71, 151 |
| abstract_inverted_index.the | 1, 43, 55, 66, 81, 144, 155, 182 |
| abstract_inverted_index.(ML) | 97 |
| abstract_inverted_index.(RL) | 13 |
| abstract_inverted_index.Deep | 8 |
| abstract_inverted_index.This | 73 |
| abstract_inverted_index.form | 56 |
| abstract_inverted_index.from | 65 |
| abstract_inverted_index.i.e. | 157 |
| abstract_inverted_index.into | 16 |
| abstract_inverted_index.like | 63 |
| abstract_inverted_index.most | 183 |
| abstract_inverted_index.that | 116, 140, 173 |
| abstract_inverted_index.this | 176 |
| abstract_inverted_index.used | 184 |
| abstract_inverted_index.well | 195 |
| abstract_inverted_index.will | 180 |
| abstract_inverted_index.with | 31, 106, 119 |
| abstract_inverted_index.agent | 29, 145 |
| abstract_inverted_index.basic | 122 |
| abstract_inverted_index.deals | 105 |
| abstract_inverted_index.games | 188 |
| abstract_inverted_index.never | 169 |
| abstract_inverted_index.paper | 75 |
| abstract_inverted_index.rapid | 5 |
| abstract_inverted_index.start | 51 |
| abstract_inverted_index.these | 27, 48 |
| abstract_inverted_index.three | 123 |
| abstract_inverted_index.trial | 36 |
| abstract_inverted_index.tried | 162, 170 |
| abstract_inverted_index.using | 150, 158 |
| abstract_inverted_index.where | 26 |
| abstract_inverted_index.which | 104 |
| abstract_inverted_index.Markov | 88 |
| abstract_inverted_index.Neural | 9 |
| abstract_inverted_index.action | 160 |
| abstract_inverted_index.agent, | 40 |
| abstract_inverted_index.agents | 114 |
| abstract_inverted_index.before | 171 |
| abstract_inverted_index.choose | 148 |
| abstract_inverted_index.error. | 38 |
| abstract_inverted_index.method | 138 |
| abstract_inverted_index.modern | 2 |
| abstract_inverted_index.offers | 76 |
| abstract_inverted_index.paper, | 178 |
| abstract_inverted_index.review | 177 |
| abstract_inverted_index.subset | 100 |
| abstract_inverted_index.Machine | 126 |
| abstract_inverted_index.actions | 168 |
| abstract_inverted_index.already | 161 |
| abstract_inverted_index.between | 149 |
| abstract_inverted_index.control | 193 |
| abstract_inverted_index.develop | 112 |
| abstract_inverted_index.discuss | 181 |
| abstract_inverted_index.evolved | 15 |
| abstract_inverted_index.improve | 117 |
| abstract_inverted_index.machine | 28 |
| abstract_inverted_index.natural | 200 |
| abstract_inverted_index.pivotal | 18 |
| abstract_inverted_index.process | 25 |
| abstract_inverted_index.refines | 70 |
| abstract_inverted_index.rewards | 59, 62 |
| abstract_inverted_index.several | 32 |
| abstract_inverted_index.through | 35, 47 |
| abstract_inverted_index.unknown | 33 |
| abstract_inverted_index.various | 92 |
| abstract_inverted_index.Decision | 89 |
| abstract_inverted_index.Learning | 12, 96, 127 |
| abstract_inverted_index.acquired | 152 |
| abstract_inverted_index.concepts | 83 |
| abstract_inverted_index.feedback | 53 |
| abstract_inverted_index.focusing | 86 |
| abstract_inverted_index.in-depth | 78 |
| abstract_inverted_index.language | 201 |
| abstract_inverted_index.learning | 24, 44, 185 |
| abstract_inverted_index.machine, | 45 |
| abstract_inverted_index.negative | 61 |
| abstract_inverted_index.positive | 58 |
| abstract_inverted_index.question | 108 |
| abstract_inverted_index.research | 74 |
| abstract_inverted_index.robotics | 189 |
| abstract_inverted_index.software | 113 |
| abstract_inverted_index.(Machine) | 115 |
| abstract_inverted_index.Networks, | 10 |
| abstract_inverted_index.Processes | 90 |
| abstract_inverted_index.behavior. | 72 |
| abstract_inverted_index.exploring | 167 |
| abstract_inverted_index.interacts | 30 |
| abstract_inverted_index.knowledge | 153 |
| abstract_inverted_index.penalties | 64 |
| abstract_inverted_index.performed | 164 |
| abstract_inverted_index.receiving | 52 |
| abstract_inverted_index.situation | 143 |
| abstract_inverted_index.‘‘the | 107 |
| abstract_inverted_index.<ol> | 129 |
| abstract_inverted_index.Artificial | 102 |
| abstract_inverted_index.algorithms | 186 |
| abstract_inverted_index.autonomous | 192 |
| abstract_inverted_index.categories | 124 |
| abstract_inverted_index.constantly | 69 |
| abstract_inverted_index.previously | 165 |
| abstract_inverted_index.responsive | 41 |
| abstract_inverted_index.</ol> | 136 |
| abstract_inverted_index.<p>In | 175 |
| abstract_inverted_index.<p>RL | 137 |
| abstract_inverted_index.development | 6 |
| abstract_inverted_index.environment | 34, 156 |
| abstract_inverted_index.healthcare, | 191 |
| abstract_inverted_index.networking, | 199 |
| abstract_inverted_index.technology. | 21 |
| abstract_inverted_index.environment, | 67 |
| abstract_inverted_index.foundational | 82 |
| abstract_inverted_index.interaction, | 49 |
| abstract_inverted_index.introduction | 79 |
| abstract_inverted_index.Intelligence, | 103 |
| abstract_inverted_index.Reinforcement | 11 |
| abstract_inverted_index.automatically | 118 |
| abstract_inverted_index.communication | 197 |
| abstract_inverted_index.are.</p> | 128 |
| abstract_inverted_index.transformative | 20 |
| abstract_inverted_index.<p>Machine | 95 |
| abstract_inverted_index.experience’’. | 120 |
| abstract_inverted_index.Learning</li> | 131, 133, 135 |
| abstract_inverted_index.<li>Supervised | 130 |
| abstract_inverted_index.situation.</p> | 174 |
| abstract_inverted_index.algorithms.</p> | 94 |
| abstract_inverted_index.<li>Unsupervised | 132 |
| abstract_inverted_index.<li>Reinforcement | 134 |
| abstract_inverted_index.processing.[1]</p> | 202 |
| cited_by_percentile_year.max | 95 |
| cited_by_percentile_year.min | 91 |
| countries_distinct_count | 1 |
| institutions_distinct_count | 3 |
| sustainable_development_goals[0].id | https://metadata.un.org/sdg/16 |
| sustainable_development_goals[0].score | 0.46000000834465027 |
| sustainable_development_goals[0].display_name | Peace, Justice and strong institutions |
| citation_normalized_percentile.value | 0.61951387 |
| citation_normalized_percentile.is_in_top_1_percent | False |
| citation_normalized_percentile.is_in_top_10_percent | False |