LEADER 01664nam 2200433Ia 450 001 996384560003316 005 20220308195225.0 035 $a(CKB)4940000000075105 035 $a(EEBO)2248551719 035 $a(OCoLC)ocm12117168e 035 $a(OCoLC)12117168 035 $a(EXLCZ)994940000000075105 100 $a19850604d1669 uy | 101 0 $aeng 135 $aurbn#|||a|bb| 200 12$aA nevv book of architecture$b[electronic resource] $ewherein is represented fourty figures of gates and arches triumphant composed of different inventions according to the five orders of columnes, viz. the Tuscane, Dorick, Ionick, Corinthian and Composite /$fby Alexander Francine ... ; with a description of each figure ; set forth by Robert Pricke for the use and benefit of all ingenious workmen that are concerned in eminent building 210 $aLondon $cPrinted by J. Darby for Robert Pricke ...$d1669 215 $a[4], xxxx p. of plates $cill., port 300 $aTranslation of: Livre d'architecture. 300 $aIllustrated t.p. 300 $aReproduction of original in Columbia University Library. 330 $aeebo-0027 606 $aGates 606 $aTriumphal arches 606 $aArchitecture$xOrders 615 0$aGates. 615 0$aTriumphal arches. 615 0$aArchitecture$xOrders. 700 $aFrancine$b Alexandre$fd. 1648.$01019570 701 $aPricke$b Robert$factive 1669-1698.$01209041 801 0$bEAA 801 1$bEAA 801 2$bm/c 801 2$bUMI 801 2$bWaOLN 906 $aBOOK 912 $a996384560003316 996 $aA nevv book of architecture$92789384 997 $aUNISA LEADER 04849nam 22007335 450 001 9911016071403321 005 20250717130246.0 010 $a3-031-94687-1 024 7 $a10.1007/978-3-031-94687-5 035 $a(MiAaPQ)EBC32223151 035 $a(Au-PeEL)EBL32223151 035 $a(CKB)39660163100041 035 $a(DE-He213)978-3-031-94687-5 035 $a(OCoLC)1530382838 035 $a(EXLCZ)9939660163100041 100 $a20250717d2025 u| 0 101 0 $aeng 135 $aurcnu|||||||| 181 $ctxt$2rdacontent 182 $cc$2rdamedia 183 $acr$2rdacarrier 200 10$aAgent AI for Finance $eFrom Financial Argument Mining to Agent-Based Modeling /$fby Chung-Chi Chen, Hiroya Takamura 205 $a1st ed. 2025. 210 1$aCham :$cSpringer Nature Switzerland :$cImprint: Springer,$d2025. 215 $a1 online resource (145 pages) 225 1 $aSpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics,$x2196-5498 311 08$a3-031-94686-3 327 $aPreface -- 1. Introduction -- 2. Financial Argument Mining -- 3. Single-Agent/Model Design -- 4. Multi-Agent Interaction -- 5. Multi-Scale Model Synergy -- 6. Generative AI Application Scenarios -- 7. Looking to the Future. 330 $aThis open access book provides an overview of the current state of financial argument mining and financial text generation, and presents the authors? thoughts on the blueprint for NLP in finance in the agent AI era. Financial documents contain numerous causal inferences and subjective opinions. In a previous book, ?From Opinion Mining to Financial Argument Mining? (Springer, 2021), the first author discussed understanding financial documents in a fine-grained manner, particularly those containing opinions. The book highlighted several future directions, such as financial argument mining, multimodal opinion understanding, and analysis generation, and anticipated a lengthy journey for these topics. However, since 2022, ChatGPT and large language models (LLMs) have shown promising advancements, motivating the authors to write this second book on the topic of financial Natural Language Processing (NLP). Agent-based AI systems have been widely discussed since the advent of LLMs. This book aims to equip researchers and practitioners with the latest methodologies, concepts, and frameworks for developing, deploying, and evaluating AI agents with capabilities in multimodal understanding, decision-making, and interaction. It places a special emphasis on human-centered decision-making and multi-agent cooperation in financial applications. The book surveys the current landscape and discuss future research and development directions. Targeting a wide audience, from students to seasoned researchers in AI and finance, this book offers an overview of recent trends in Agent AI for finance. It provides a foundation for students to understand the field and design their research direction, while inviting experienced researchers to engage in discussions on open research questions informed by pilot experimental results. Although this book focuses on financial applications, the discussed concepts and methods can also be applied to other real-world applications by integrating domain-specific characteristics. The authors look forward to seeing new findings and more novel extensions based on the proposed ideas. 410 0$aSpringerBriefs in Intelligent Systems, Artificial Intelligence, Multiagent Systems, and Cognitive Robotics,$x2196-5498 606 $aArtificial intelligence 606 $aMultiagent systems 606 $aMachine learning 606 $aBusiness$xData processing 606 $aBusiness information services 606 $aNatural language processing (Computer science) 606 $aArtificial Intelligence 606 $aMultiagent Systems 606 $aMachine Learning 606 $aBusiness Analytics 606 $aBusiness Information Systems 606 $aNatural Language Processing (NLP) 615 0$aArtificial intelligence. 615 0$aMultiagent systems. 615 0$aMachine learning. 615 0$aBusiness$xData processing. 615 0$aBusiness information services. 615 0$aNatural language processing (Computer science) 615 14$aArtificial Intelligence. 615 24$aMultiagent Systems. 615 24$aMachine Learning. 615 24$aBusiness Analytics. 615 24$aBusiness Information Systems. 615 24$aNatural Language Processing (NLP). 676 $a006.3 700 $aChen$b Chung-Chi$0906903 701 $aTakamura$b Hiroya$01834447 801 0$bMiAaPQ 801 1$bMiAaPQ 801 2$bMiAaPQ 906 $aBOOK 912 $a9911016071403321 996 $aAgent AI for Finance$94409937 997 $aUNINA