Enhancing automated decision-making through AI:
"Computational capabilities bring with them the advantages of cold logic, precision, speed, data omniscience, mass data processing capabilities, multimodality, enriched deployments, and efficiencies. With these many advantages, people seek to offload work to machines. Now with the major advance...
Saved in:
| Main Author: | |
|---|---|
| Format: | Electronic eBook |
| Language: | English |
| Published: |
Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA)
IGI Global
2025.
|
| Series: | Advances in computational intelligence and robotics (ACIR) book series.
|
| Subjects: | |
| Online Access: | DE-862 DE-863 |
| Summary: | "Computational capabilities bring with them the advantages of cold logic, precision, speed, data omniscience, mass data processing capabilities, multimodality, enriched deployments, and efficiencies. With these many advantages, people seek to offload work to machines. Now with the major advances in artificial intelligence, humanity is moving closer to handing over complex decision-making to machines, without humans in the direct loop. Enhancing Automated Decision-Making Through AI explores the processes of designing and deploying systems for automated decision-making. It also considers the implications of automated decision-making informed by AI, which can be unpredictable. Covering topics such as agriculture, disaster detection, and tumor detection, this book is an excellent resource for engineers, systems designers, instructors, graduate and postgraduate students, and more."-- |
| Physical Description: | 27 PDFs (600 Seiten) Also available in print. |
| Format: | Mode of access: World Wide Web. |
| Bibliography: | Includes bibliographical references and index. |
| ISBN: | 9798369362327 |
| Access: | Restricted to subscribers or individual electronic text purchasers. |
Staff View
MARC
| LEADER | 00000nam a2200000 i 4500 | ||
|---|---|---|---|
| 001 | ZDB-98-IGB-00343250 | ||
| 003 | IGIG | ||
| 005 | 20241209134413.0 | ||
| 006 | m eo d | ||
| 007 | cr bn||||m|||a | ||
| 008 | 241209s2025 pau fob 001 0 eng d | ||
| 020 | |a 9798369362327 |q PDF | ||
| 020 | |z 9798369362303 |q print | ||
| 024 | 7 | |a 10.4018/979-8-3693-6230-3 |2 doi | |
| 035 | |a (CaBNVSL)slc00007186 | ||
| 035 | |a (OCoLC)1479494646 | ||
| 040 | |a CaBNVSL |b eng |e rda |c CaBNVSL |d CaBNVSL | ||
| 050 | 4 | |a QA402.3 |b .H35 2025e | |
| 082 | 7 | |a 629.8312 |2 23 | |
| 100 | 1 | |a Hai-Jew, Shalin, |e author. | |
| 245 | 1 | 0 | |a Enhancing automated decision-making through AI |c Shalin Hai-Jew. |
| 246 | 3 | |a Enhancing automated decision-making through artificial intelligence | |
| 264 | 1 | |a Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) |b IGI Global |c 2025. | |
| 300 | |a 27 PDFs (600 Seiten) | ||
| 336 | |a text |2 rdacontent | ||
| 337 | |a electronic |2 isbdmedia | ||
| 338 | |a online resource |2 rdacarrier | ||
| 490 | 1 | |a Advances in computational intelligence and robotics (ACIR) book series | |
| 504 | |a Includes bibliographical references and index. | ||
| 505 | 0 | |a Preface -- Acknowledgment -- Section 1. Applied AI Decision-Making -- Chapter 1. The Impact and Evolution of Deep Learning in Contemporary Real-World Predictive Applications: Diving Deep -- Chapter 2. Transitioning From Legacy Systems to AI: A Holistic Approach to Disaster Detection -- Chapter 3. AI-Powered IoT (AI IoT) for Decision-Making in Smart Agriculture: KSK Approach for Smart Agriculture -- Chapter 4. Optimizing Performance Metrics in Blockchain-Enabled AI/ML Data Analytics: Assessing Cognitive IoT -- Section 2. Cases of Applied AI Decision-Making -- Chapter 5. Classification and Predicting Abundance of Anopheles Mosquitoes in Zimbabwe Using Machine Learning -- Chapter 6. AI and IoT Solutions for Food Security and Agriculture -- Chapter 7. Role of Multi-Agent System in Reducing Failure Probabilities in Production System -- Section 3. Learning and Prediction With AI -- Chapter 8. Harnessing AI for Automated Decision-Making in Farm Machinery and Operations: Optimizing Agriculture -- Chapter 9. Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models -- Chapter 10. Machine Learning Model to Predict Gold Prices for Zimbabwean Economy -- Chapter 11. Indian Legal Documents Corpus for Court Judgment Prediction and Summarization: CJPS -- Section 4. Ethics in AI Decision-Making -- Chapter 12. Ethics in AI and Computation in Automated Decision-Making -- Chapter 13. Navigating the Ethical Frontier-Human Oversight in AI-Driven Decision-Making System -- Section 5. Thought Experiments in AI for Committed Decision-Making -- Chapter 14. Exploring Generative AI as Personally Effective Decision-Making Tools: A Thought Experiment -- Compilation of References -- About the Contributors -- Index. | |
| 506 | |a Restricted to subscribers or individual electronic text purchasers. | ||
| 520 | 3 | |a "Computational capabilities bring with them the advantages of cold logic, precision, speed, data omniscience, mass data processing capabilities, multimodality, enriched deployments, and efficiencies. With these many advantages, people seek to offload work to machines. Now with the major advances in artificial intelligence, humanity is moving closer to handing over complex decision-making to machines, without humans in the direct loop. Enhancing Automated Decision-Making Through AI explores the processes of designing and deploying systems for automated decision-making. It also considers the implications of automated decision-making informed by AI, which can be unpredictable. Covering topics such as agriculture, disaster detection, and tumor detection, this book is an excellent resource for engineers, systems designers, instructors, graduate and postgraduate students, and more."-- |c Provided by publisher. | |
| 530 | |a Also available in print. | ||
| 538 | |a Mode of access: World Wide Web. | ||
| 588 | |a Description based on title screen (IGI Global, viewed 12/09/2024). | ||
| 650 | 0 | |a Artificial intelligence. | |
| 650 | 0 | |a Control theory. | |
| 650 | 0 | |a Decision making. | |
| 650 | 0 | |a Operations research. | |
| 650 | 0 | |a Problem solving. | |
| 653 | |a Agriculture. | ||
| 653 | |a Artificial Intelligence (AI) | ||
| 653 | |a Automation. | ||
| 653 | |a Blockchain Technology. | ||
| 653 | |a Decision-Making Tools. | ||
| 653 | |a Deep Learning Models. | ||
| 653 | |a Disaster Detection. | ||
| 653 | |a Food Security. | ||
| 653 | |a Internet of Things (IoT) | ||
| 653 | |a Machine Learning (ML) | ||
| 653 | |a Performance Metrics. | ||
| 653 | |a Predictive Applications. | ||
| 653 | |a Tumor Detection. | ||
| 655 | 4 | |a Electronic books. | |
| 710 | 2 | |a IGI Global, |e publisher. | |
| 776 | 0 | 8 | |i Print version: |z 9798369362303 |
| 830 | 0 | |a Advances in computational intelligence and robotics (ACIR) book series. | |
| 966 | 4 | 0 | |l DE-862 |p ZDB-98-IGB |q FWS_PDA_IGB |u https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-6230-3 |3 Volltext |
| 966 | 4 | 0 | |l DE-863 |p ZDB-98-IGB |q FWS_PDA_IGB |u https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-6230-3 |3 Volltext |
| 912 | |a ZDB-98-IGB | ||
| 049 | |a DE-862 | ||
| 049 | |a DE-863 | ||
Record in the Search Index
| DE-BY-FWS_katkey | ZDB-98-IGB-00343250 |
|---|---|
| _version_ | 1826942603793268736 |
| adam_text | |
| any_adam_object | |
| author | Hai-Jew, Shalin |
| author_facet | Hai-Jew, Shalin |
| author_role | aut |
| author_sort | Hai-Jew, Shalin |
| author_variant | s h j shj |
| building | Verbundindex |
| bvnumber | localFWS |
| callnumber-first | Q - Science |
| callnumber-label | QA402 |
| callnumber-raw | QA402.3 .H35 2025e |
| callnumber-search | QA402.3 .H35 2025e |
| callnumber-sort | QA 3402.3 H35 42025E |
| callnumber-subject | QA - Mathematics |
| collection | ZDB-98-IGB |
| contents | Preface -- Acknowledgment -- Section 1. Applied AI Decision-Making -- Chapter 1. The Impact and Evolution of Deep Learning in Contemporary Real-World Predictive Applications: Diving Deep -- Chapter 2. Transitioning From Legacy Systems to AI: A Holistic Approach to Disaster Detection -- Chapter 3. AI-Powered IoT (AI IoT) for Decision-Making in Smart Agriculture: KSK Approach for Smart Agriculture -- Chapter 4. Optimizing Performance Metrics in Blockchain-Enabled AI/ML Data Analytics: Assessing Cognitive IoT -- Section 2. Cases of Applied AI Decision-Making -- Chapter 5. Classification and Predicting Abundance of Anopheles Mosquitoes in Zimbabwe Using Machine Learning -- Chapter 6. AI and IoT Solutions for Food Security and Agriculture -- Chapter 7. Role of Multi-Agent System in Reducing Failure Probabilities in Production System -- Section 3. Learning and Prediction With AI -- Chapter 8. Harnessing AI for Automated Decision-Making in Farm Machinery and Operations: Optimizing Agriculture -- Chapter 9. Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models -- Chapter 10. Machine Learning Model to Predict Gold Prices for Zimbabwean Economy -- Chapter 11. Indian Legal Documents Corpus for Court Judgment Prediction and Summarization: CJPS -- Section 4. Ethics in AI Decision-Making -- Chapter 12. Ethics in AI and Computation in Automated Decision-Making -- Chapter 13. Navigating the Ethical Frontier-Human Oversight in AI-Driven Decision-Making System -- Section 5. Thought Experiments in AI for Committed Decision-Making -- Chapter 14. Exploring Generative AI as Personally Effective Decision-Making Tools: A Thought Experiment -- Compilation of References -- About the Contributors -- Index. |
| ctrlnum | (CaBNVSL)slc00007186 (OCoLC)1479494646 |
| dewey-full | 629.8312 |
| dewey-hundreds | 600 - Technology (Applied sciences) |
| dewey-ones | 629 - Other branches of engineering |
| dewey-raw | 629.8312 |
| dewey-search | 629.8312 |
| dewey-sort | 3629.8312 |
| dewey-tens | 620 - Engineering and allied operations |
| discipline | Mess-/Steuerungs-/Regelungs-/Automatisierungstechnik / Mechatronik |
| format | Electronic eBook |
| fullrecord | <?xml version="1.0" encoding="UTF-8"?><collection xmlns="http://www.loc.gov/MARC21/slim"><record><leader>05063nam a2200661 i 4500</leader><controlfield tag="001">ZDB-98-IGB-00343250</controlfield><controlfield tag="003">IGIG</controlfield><controlfield tag="005">20241209134413.0</controlfield><controlfield tag="006">m eo d </controlfield><controlfield tag="007">cr bn||||m|||a</controlfield><controlfield tag="008">241209s2025 pau fob 001 0 eng d</controlfield><datafield tag="020" ind1=" " ind2=" "><subfield code="a">9798369362327</subfield><subfield code="q">PDF</subfield></datafield><datafield tag="020" ind1=" " ind2=" "><subfield code="z">9798369362303</subfield><subfield code="q">print</subfield></datafield><datafield tag="024" ind1="7" ind2=" "><subfield code="a">10.4018/979-8-3693-6230-3</subfield><subfield code="2">doi</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(CaBNVSL)slc00007186</subfield></datafield><datafield tag="035" ind1=" " ind2=" "><subfield code="a">(OCoLC)1479494646</subfield></datafield><datafield tag="040" ind1=" " ind2=" "><subfield code="a">CaBNVSL</subfield><subfield code="b">eng</subfield><subfield code="e">rda</subfield><subfield code="c">CaBNVSL</subfield><subfield code="d">CaBNVSL</subfield></datafield><datafield tag="050" ind1=" " ind2="4"><subfield code="a">QA402.3</subfield><subfield code="b">.H35 2025e</subfield></datafield><datafield tag="082" ind1="7" ind2=" "><subfield code="a">629.8312</subfield><subfield code="2">23</subfield></datafield><datafield tag="100" ind1="1" ind2=" "><subfield code="a">Hai-Jew, Shalin,</subfield><subfield code="e">author.</subfield></datafield><datafield tag="245" ind1="1" ind2="0"><subfield code="a">Enhancing automated decision-making through AI </subfield><subfield code="c">Shalin Hai-Jew.</subfield></datafield><datafield tag="246" ind1="3" ind2=" "><subfield code="a">Enhancing automated decision-making through artificial intelligence</subfield></datafield><datafield tag="264" ind1=" " ind2="1"><subfield code="a">Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) </subfield><subfield code="b">IGI Global</subfield><subfield code="c">2025.</subfield></datafield><datafield tag="300" ind1=" " ind2=" "><subfield code="a">27 PDFs (600 Seiten)</subfield></datafield><datafield tag="336" ind1=" " ind2=" "><subfield code="a">text</subfield><subfield code="2">rdacontent</subfield></datafield><datafield tag="337" ind1=" " ind2=" "><subfield code="a">electronic</subfield><subfield code="2">isbdmedia</subfield></datafield><datafield tag="338" ind1=" " ind2=" "><subfield code="a">online resource</subfield><subfield code="2">rdacarrier</subfield></datafield><datafield tag="490" ind1="1" ind2=" "><subfield code="a">Advances in computational intelligence and robotics (ACIR) book series</subfield></datafield><datafield tag="504" ind1=" " ind2=" "><subfield code="a">Includes bibliographical references and index.</subfield></datafield><datafield tag="505" ind1="0" ind2=" "><subfield code="a">Preface -- Acknowledgment -- Section 1. Applied AI Decision-Making -- Chapter 1. The Impact and Evolution of Deep Learning in Contemporary Real-World Predictive Applications: Diving Deep -- Chapter 2. Transitioning From Legacy Systems to AI: A Holistic Approach to Disaster Detection -- Chapter 3. AI-Powered IoT (AI IoT) for Decision-Making in Smart Agriculture: KSK Approach for Smart Agriculture -- Chapter 4. Optimizing Performance Metrics in Blockchain-Enabled AI/ML Data Analytics: Assessing Cognitive IoT -- Section 2. Cases of Applied AI Decision-Making -- Chapter 5. Classification and Predicting Abundance of Anopheles Mosquitoes in Zimbabwe Using Machine Learning -- Chapter 6. AI and IoT Solutions for Food Security and Agriculture -- Chapter 7. Role of Multi-Agent System in Reducing Failure Probabilities in Production System -- Section 3. Learning and Prediction With AI -- Chapter 8. Harnessing AI for Automated Decision-Making in Farm Machinery and Operations: Optimizing Agriculture -- Chapter 9. Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models -- Chapter 10. Machine Learning Model to Predict Gold Prices for Zimbabwean Economy -- Chapter 11. Indian Legal Documents Corpus for Court Judgment Prediction and Summarization: CJPS -- Section 4. Ethics in AI Decision-Making -- Chapter 12. Ethics in AI and Computation in Automated Decision-Making -- Chapter 13. Navigating the Ethical Frontier-Human Oversight in AI-Driven Decision-Making System -- Section 5. Thought Experiments in AI for Committed Decision-Making -- Chapter 14. Exploring Generative AI as Personally Effective Decision-Making Tools: A Thought Experiment -- Compilation of References -- About the Contributors -- Index.</subfield></datafield><datafield tag="506" ind1=" " ind2=" "><subfield code="a">Restricted to subscribers or individual electronic text purchasers.</subfield></datafield><datafield tag="520" ind1="3" ind2=" "><subfield code="a">"Computational capabilities bring with them the advantages of cold logic, precision, speed, data omniscience, mass data processing capabilities, multimodality, enriched deployments, and efficiencies. With these many advantages, people seek to offload work to machines. Now with the major advances in artificial intelligence, humanity is moving closer to handing over complex decision-making to machines, without humans in the direct loop. Enhancing Automated Decision-Making Through AI explores the processes of designing and deploying systems for automated decision-making. It also considers the implications of automated decision-making informed by AI, which can be unpredictable. Covering topics such as agriculture, disaster detection, and tumor detection, this book is an excellent resource for engineers, systems designers, instructors, graduate and postgraduate students, and more."--</subfield><subfield code="c">Provided by publisher.</subfield></datafield><datafield tag="530" ind1=" " ind2=" "><subfield code="a">Also available in print.</subfield></datafield><datafield tag="538" ind1=" " ind2=" "><subfield code="a">Mode of access: World Wide Web.</subfield></datafield><datafield tag="588" ind1=" " ind2=" "><subfield code="a">Description based on title screen (IGI Global, viewed 12/09/2024).</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Artificial intelligence.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Control theory.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Decision making.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Operations research.</subfield></datafield><datafield tag="650" ind1=" " ind2="0"><subfield code="a">Problem solving.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Agriculture.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Artificial Intelligence (AI)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Automation.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Blockchain Technology.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Decision-Making Tools.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Deep Learning Models.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Disaster Detection.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Food Security.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Internet of Things (IoT)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Machine Learning (ML)</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Performance Metrics.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Predictive Applications.</subfield></datafield><datafield tag="653" ind1=" " ind2=" "><subfield code="a">Tumor Detection.</subfield></datafield><datafield tag="655" ind1=" " ind2="4"><subfield code="a">Electronic books.</subfield></datafield><datafield tag="710" ind1="2" ind2=" "><subfield code="a">IGI Global,</subfield><subfield code="e">publisher.</subfield></datafield><datafield tag="776" ind1="0" ind2="8"><subfield code="i">Print version:</subfield><subfield code="z">9798369362303</subfield></datafield><datafield tag="830" ind1=" " ind2="0"><subfield code="a">Advances in computational intelligence and robotics (ACIR) book series.</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-862</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="q">FWS_PDA_IGB</subfield><subfield code="u">https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-6230-3</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="966" ind1="4" ind2="0"><subfield code="l">DE-863</subfield><subfield code="p">ZDB-98-IGB</subfield><subfield code="q">FWS_PDA_IGB</subfield><subfield code="u">https://services.igi-global.com/resolvedoi/resolve.aspx?doi=10.4018/979-8-3693-6230-3</subfield><subfield code="3">Volltext</subfield></datafield><datafield tag="912" ind1=" " ind2=" "><subfield code="a">ZDB-98-IGB</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-862</subfield></datafield><datafield tag="049" ind1=" " ind2=" "><subfield code="a">DE-863</subfield></datafield></record></collection> |
| genre | Electronic books. |
| genre_facet | Electronic books. |
| id | ZDB-98-IGB-00343250 |
| illustrated | Not Illustrated |
| indexdate | 2025-03-18T14:30:38Z |
| institution | BVB |
| isbn | 9798369362327 |
| language | English |
| oclc_num | 1479494646 |
| open_access_boolean | |
| owner | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| owner_facet | DE-862 DE-BY-FWS DE-863 DE-BY-FWS |
| physical | 27 PDFs (600 Seiten) Also available in print. |
| psigel | ZDB-98-IGB FWS_PDA_IGB ZDB-98-IGB |
| publishDate | 2025 |
| publishDateSearch | 2025 |
| publishDateSort | 2025 |
| publisher | IGI Global |
| record_format | marc |
| series | Advances in computational intelligence and robotics (ACIR) book series. |
| series2 | Advances in computational intelligence and robotics (ACIR) book series |
| spelling | Hai-Jew, Shalin, author. Enhancing automated decision-making through AI Shalin Hai-Jew. Enhancing automated decision-making through artificial intelligence Hershey, Pennsylvania (701 E. Chocolate Avenue, Hershey, Pennsylvania, 17033, USA) IGI Global 2025. 27 PDFs (600 Seiten) text rdacontent electronic isbdmedia online resource rdacarrier Advances in computational intelligence and robotics (ACIR) book series Includes bibliographical references and index. Preface -- Acknowledgment -- Section 1. Applied AI Decision-Making -- Chapter 1. The Impact and Evolution of Deep Learning in Contemporary Real-World Predictive Applications: Diving Deep -- Chapter 2. Transitioning From Legacy Systems to AI: A Holistic Approach to Disaster Detection -- Chapter 3. AI-Powered IoT (AI IoT) for Decision-Making in Smart Agriculture: KSK Approach for Smart Agriculture -- Chapter 4. Optimizing Performance Metrics in Blockchain-Enabled AI/ML Data Analytics: Assessing Cognitive IoT -- Section 2. Cases of Applied AI Decision-Making -- Chapter 5. Classification and Predicting Abundance of Anopheles Mosquitoes in Zimbabwe Using Machine Learning -- Chapter 6. AI and IoT Solutions for Food Security and Agriculture -- Chapter 7. Role of Multi-Agent System in Reducing Failure Probabilities in Production System -- Section 3. Learning and Prediction With AI -- Chapter 8. Harnessing AI for Automated Decision-Making in Farm Machinery and Operations: Optimizing Agriculture -- Chapter 9. Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models -- Chapter 10. Machine Learning Model to Predict Gold Prices for Zimbabwean Economy -- Chapter 11. Indian Legal Documents Corpus for Court Judgment Prediction and Summarization: CJPS -- Section 4. Ethics in AI Decision-Making -- Chapter 12. Ethics in AI and Computation in Automated Decision-Making -- Chapter 13. Navigating the Ethical Frontier-Human Oversight in AI-Driven Decision-Making System -- Section 5. Thought Experiments in AI for Committed Decision-Making -- Chapter 14. Exploring Generative AI as Personally Effective Decision-Making Tools: A Thought Experiment -- Compilation of References -- About the Contributors -- Index. Restricted to subscribers or individual electronic text purchasers. "Computational capabilities bring with them the advantages of cold logic, precision, speed, data omniscience, mass data processing capabilities, multimodality, enriched deployments, and efficiencies. With these many advantages, people seek to offload work to machines. Now with the major advances in artificial intelligence, humanity is moving closer to handing over complex decision-making to machines, without humans in the direct loop. Enhancing Automated Decision-Making Through AI explores the processes of designing and deploying systems for automated decision-making. It also considers the implications of automated decision-making informed by AI, which can be unpredictable. Covering topics such as agriculture, disaster detection, and tumor detection, this book is an excellent resource for engineers, systems designers, instructors, graduate and postgraduate students, and more."-- Provided by publisher. Also available in print. Mode of access: World Wide Web. Description based on title screen (IGI Global, viewed 12/09/2024). Artificial intelligence. Control theory. Decision making. Operations research. Problem solving. Agriculture. Artificial Intelligence (AI) Automation. Blockchain Technology. Decision-Making Tools. Deep Learning Models. Disaster Detection. Food Security. Internet of Things (IoT) Machine Learning (ML) Performance Metrics. Predictive Applications. Tumor Detection. Electronic books. IGI Global, publisher. Print version: 9798369362303 Advances in computational intelligence and robotics (ACIR) book series. |
| spellingShingle | Hai-Jew, Shalin Enhancing automated decision-making through AI Advances in computational intelligence and robotics (ACIR) book series. Preface -- Acknowledgment -- Section 1. Applied AI Decision-Making -- Chapter 1. The Impact and Evolution of Deep Learning in Contemporary Real-World Predictive Applications: Diving Deep -- Chapter 2. Transitioning From Legacy Systems to AI: A Holistic Approach to Disaster Detection -- Chapter 3. AI-Powered IoT (AI IoT) for Decision-Making in Smart Agriculture: KSK Approach for Smart Agriculture -- Chapter 4. Optimizing Performance Metrics in Blockchain-Enabled AI/ML Data Analytics: Assessing Cognitive IoT -- Section 2. Cases of Applied AI Decision-Making -- Chapter 5. Classification and Predicting Abundance of Anopheles Mosquitoes in Zimbabwe Using Machine Learning -- Chapter 6. AI and IoT Solutions for Food Security and Agriculture -- Chapter 7. Role of Multi-Agent System in Reducing Failure Probabilities in Production System -- Section 3. Learning and Prediction With AI -- Chapter 8. Harnessing AI for Automated Decision-Making in Farm Machinery and Operations: Optimizing Agriculture -- Chapter 9. Automated Brain Tumor Detection From Magnetic Resonance Imaging Using AI-PSO-Based Deep Learning Models -- Chapter 10. Machine Learning Model to Predict Gold Prices for Zimbabwean Economy -- Chapter 11. Indian Legal Documents Corpus for Court Judgment Prediction and Summarization: CJPS -- Section 4. Ethics in AI Decision-Making -- Chapter 12. Ethics in AI and Computation in Automated Decision-Making -- Chapter 13. Navigating the Ethical Frontier-Human Oversight in AI-Driven Decision-Making System -- Section 5. Thought Experiments in AI for Committed Decision-Making -- Chapter 14. Exploring Generative AI as Personally Effective Decision-Making Tools: A Thought Experiment -- Compilation of References -- About the Contributors -- Index. Artificial intelligence. Control theory. Decision making. Operations research. Problem solving. |
| title | Enhancing automated decision-making through AI |
| title_alt | Enhancing automated decision-making through artificial intelligence |
| title_auth | Enhancing automated decision-making through AI |
| title_exact_search | Enhancing automated decision-making through AI |
| title_full | Enhancing automated decision-making through AI Shalin Hai-Jew. |
| title_fullStr | Enhancing automated decision-making through AI Shalin Hai-Jew. |
| title_full_unstemmed | Enhancing automated decision-making through AI Shalin Hai-Jew. |
| title_short | Enhancing automated decision-making through AI |
| title_sort | enhancing automated decision making through ai |
| topic | Artificial intelligence. Control theory. Decision making. Operations research. Problem solving. |
| topic_facet | Artificial intelligence. Control theory. Decision making. Operations research. Problem solving. Electronic books. |
| work_keys_str_mv | AT haijewshalin enhancingautomateddecisionmakingthroughai AT igiglobal enhancingautomateddecisionmakingthroughai AT haijewshalin enhancingautomateddecisionmakingthroughartificialintelligence AT igiglobal enhancingautomateddecisionmakingthroughartificialintelligence |