{"product_id":"artificial-intelligence-logic-and-applications-9789819603534","title":"Artificial Intelligence Logic and Applications","description":"\u003cb\u003eBook Synopsis\u003c\/b\u003e\u003cbr\u003e\u003cp\u003e\u003cstrong\u003e.- AI Logic Foundation.\u003c\/strong\u003e\u003cbr\u003e.- Game Semantics for Modal Logic with Counting.\u003cbr\u003e.- Adding concurrency to Quantum Dynamic Logic.\u003cbr\u003e.- Lattices for Many-logics Modal Logic: constructions and representations.\u003cbr\u003e.- A note to the construction of t-norms based on T nM.\u003cbr\u003e.- Conditional Distributivity of S-uninorms and T-uninorms over Uninorms.\u003cbr\u003e.- Fuzzy Integrals Induced From Semi-Quasi-Overlap (Grouping) Functions.\u003cbr\u003e.- The Research on the multi-agent argumentation Semantics.\u003cbr\u003e.- An exercise in Uppaal: Modelling the circadian clock of a cyanobacteria.\u003cbr\u003e\u003cstrong\u003e.- AI Logic Reasoning.\u003c\/strong\u003e\u003cbr\u003e.- Semi-Quasi-Overlap Functions and Their Applications in Classifier Ensemble.\u003cbr\u003e.- Data and Knowledge Dual-Driven Traffic Sign Recognition Algorithm.\u003cbr\u003e.- Automatic Inspection of Static Application Security Testing (SAST) Reports via Large Language Model Reasoning.\u003cbr\u003e.- Semantic Abstractions for Multi-label Classification.\u003cbr\u003e.- Multi-granularity Semantic Representation and Rule-based Labeling for Relation Classification.\u003cbr\u003e\u003cstrong\u003e.- AI Logic Applications.\u003c\/strong\u003e\u003cbr\u003e.- Feature Representation Learning based on Graph Curvature-revised Deep Graph Learning.\u003cbr\u003e.- Non-negative Tensor Representation and Unsupervised Classification of Object Pose in Continuous Image Sequences.\u003cbr\u003e.- An Optimal Scheduling Algorithm for Intelligent Embedded Heterogeneous Multicore System.\u003cbr\u003e.- Kernel Cutset-type Possibility C-Means Algorithm for Gaussian Granularity. \u003cbr\u003e.- Research on Fusion Modeling for Active Magnetic Bearings Based on Mechanism and Data Driven.\u003cbr\u003e.- Multi-Objective Waterborne Trash Tracking based on D-StrongSORT.\u003cbr\u003e.- A Contributor-Based Segmentation Model for Open Source Software Source Code Trustworthiness Measurement.\u003cbr\u003e.- Facilitating the Propagation of Oscillatory Signals in Cortical Networks through Mixed Resonance.\u003cbr\u003e.- An Empirical Study for Source Code Incompatibility Between Versions of Java Open-Source Software.\u003cbr\u003e.- Exploring Multi-source Mobile Applications Association Discovery Based on Representation Learning.\u003cbr\u003e.- TakagiSugeno Target Recognition Algorithm Based on Global Intuitionistic Fuzzy Method.\u003cbr\u003e.- Automated Legality Detection on Privacy Policy Based on Deep Learning.\u003cbr\u003e.- CNN lung sound recognition and classification model based on multi-feature fusion and data enhancement.\u003cbr\u003e.- The Specialization of AGI: Exploration of Industrial Applications for General Artificial Intelligence.\u003c\/p\u003e","brand":"Springer","offers":[{"title":"Default Title","offer_id":53212865397079,"sku":"9789819603534","price":64.99,"currency_code":"GBP","in_stock":true}],"url":"https:\/\/bookcurl.com\/products\/artificial-intelligence-logic-and-applications-9789819603534","provider":"Book Curl","version":"1.0","type":"link"}