| Autore |
Abe Jair Minoro
|
| Edizione | [1st ed.] |
| Pubbl/distr/stampa |
Cham : , : Springer International Publishing AG, , 2023
|
| Descrizione fisica |
1 online resource (210 pages)
|
| Disciplina |
006.3
|
| Collana |
Intelligent Systems Reference Library
|
| ISBN |
3-031-35759-0
|
| Formato |
Materiale a stampa  |
| Livello bibliografico |
Monografia |
| Lingua di pubblicazione |
eng
|
| Nota di contenuto |
Intro -- Preface -- Contents -- Contributors -- 1 The Scientific Work of Seiki Akama -- 1.1 Introduction -- 1.2 Biographical Information -- 1.3 Scientific Work -- 1.4 Books -- References -- 2 A Busy-Beaver-Like Function in Complexity Theory -- 2.1 Introduction -- 2.2 Required Notation and Concepts: Function F -- 2.3 Kreisel's Counterexample Function to [P=NP] -- 2.4 Main Steps in Our Argument -- 2.5 The Crucial Step -- 2.6 f Is a Busy-Beaver-Like Function -- 2.7 Proof of Kreisel's Conjecture for f -- 2.8 More Exoticisms -- 2.9 Envoi -- References -- 3 On the Choice of Primitives in Tense Logic -- 3.1 Introduction -- 3.2 Basic Tense Logic -- 3.3 Alternative Axiomatization -- References -- 4 Paraconsistent Annotated Logic and Chaos Theory: Introducing the Fundamental Equations -- 4.1 Introduction -- 4.1.1 Literature Review -- 4.1.2 Non-Classical Paraconsistent Logic (PL) -- 4.2 The Logistic Map Equation and the Foundations of PAL2v -- 4.2.1 The ParaChaos Equations -- 4.2.2 Paraconsistent/Chaos Theory Equilibrium Point of Reference -- 4.3 Results of an Application of the ParaChaos Equations -- 4.3.1 Computer Simulations Results -- 4.4 Conclusions -- References -- 5 A Paraconsistent Artificial Neural Cell of Learning by Contradiction Extraction (PANCLCTX) with Application Examples -- 5.1 Introduction -- 5.2 Paraconsistent Logic (PL) -- 5.2.1 Paraconsistent Artificial Neural Cell -- 5.2.2 Paraconsistent Artificial Neural Cell of Learning -- 5.3 Paraconsistent Artificial Neural Cell of Learning by Contradiction Extraction -- 5.4 Application Examples in the Industry -- 5.4.1 Variable Estimator Configured with PANCLCTX -- 5.4.2 Average Extractor with PANCLCTX -- 5.4.3 Temperature Measurement with PANCLCTX -- 5.5 Conclusions -- References -- 6 Probabilistic Autoepistemic Equilibrium Logic -- 6.1 Syntax and Semantics of PE.
6.2 Probabilistic Autoepistemic Equilibrium Logic -- 6.3 Conclusions -- References -- 7 Rough-Set-Base Data Analysis: Theoretical Basis and Applications -- 7.1 Introduction -- 7.2 Rough Sets -- 7.2.1 Decision Table and Lower and Upper Approximations -- 7.2.2 Relative Reduct -- 7.2.3 Discernibility Matrix -- 7.2.4 Decision Rule -- 7.3 Heuristic Algorithm for Attribute Reduction Using Reduced Decision Tables -- 7.3.1 Conclusion of Section 7.3 -- 7.4 Evaluation of Relative Reducts Using Partitions -- 7.4.1 Roughness of Partition and Average of Coverage of Decision Rules -- 7.4.2 Example -- 7.4.3 Conclusion of Section 7.4 -- 7.5 An Example of Applications-Rough-Set-Based DNA Data Analysis -- 7.5.1 Background -- 7.5.2 Methodology -- 7.5.3 Datasets -- 7.5.4 Results and Discussion -- 7.5.5 Conclusion of Section 7.5 -- 7.6 Summary -- References -- 8 Bilattice Tableau Calculi with Rough Set Semantics -- 8.1 Introduction -- 8.2 Rough Set and Decision Logic -- 8.3 Four-Valued Logic and Bilattice -- 8.3.1 Belnap's Four-Valued Logic -- 8.3.2 Rough Sets Semantics for Bilattice -- 8.4 Bilattice-Based Tableau Calculi -- 8.5 Soundness and Completeness -- 8.6 Conclusion -- References -- 9 Optimizing the Data Loss Prevention Level Using Logic Paraconsistent Annotated Evidential Eτ -- 9.1 Introduction -- 9.1.1 General Context -- 9.1.2 General Data Protection Law of Brazil -- 9.1.3 Artificial Intelligence -- 9.1.4 Machine Learning -- 9.2 Bibliographic Review -- 9.2.1 DLP-Data Loss Prevention -- 9.2.2 Paraconsistent Annotated Evidential Logic Eτ -- 9.2.3 Artificial Intelligence Techniques -- 9.2.4 Data Protection -- 9.3 Minimization of Data Loss -- 9.3.1 DLP-Data Loss Prevention Using Paraconsistent Annotated Evidential Logic Eτ -- 9.4 Tests -- 9.4.1 Python Program and Mass Data Results -- 9.5 Conclusion -- References.
10 Evaluation of Behavioural Skills Simulating Hiring of Project Manager Applying Paraconsistent Annotated Evidential Logic Eτ -- 10.1 Introduction -- 10.2 Selection Process -- 10.2.1 Interview -- 10.2.2 The Project Manager Candidate -- 10.2.3 Simulation -- 10.3 Paraconsistent Annotated Evidential Logic Eτ -- 10.4 Method -- 10.4.1 The Hypothetical Scenario -- 10.4.2 Expert Groups -- 10.4.3 Logic E Application Evaluating Candidate -- 10.5 Result -- 10.6 Discussion -- 10.7 Conclusion -- References -- 11 A Paraconsistent Decision-Making Method -- 11.1 Introduction -- 11.2 The Unitary Square of the Cartesian Plane (USCP) -- 11.3 Decision Rule -- 11.4 NOT, OR and AND Operators of Logic Eτ -- 11.5 The Decision Making Process: Paraconsistent Decision-Making Method (PDM) -- 11.5.1 The Stages of the PDM -- 11.5.2 Analysis of Results -- 11.6 Conclusions and Observations -- References -- 12 Annotated Logics and Application-An Overview -- 12.1 Introduction -- 12.1.1 Paraconsistent Logic -- 12.1.2 Initial Indirect Applications of Paconsistent Logics -- 12.1.3 Inheritance Nets -- 12.1.4 Object Oriented Database -- 12.2 Some Subsequent Applications -- 12.2.1 Logic Programming -- 12.2.2 Paraconsistent Annotated Evidential Logic Eτ -- 12.2.3 Expert Systems -- 12.2.4 Automatic Prediction of Stress in Piglets (Sus Scrofa) -- 12.2.5 Model for Paraconsistent Quality Assessment of Software Developed in Salesforce -- 12.2.6 About the Turning Point of Cache Efficiency in Computer Networks with Logic Eτ -- 12.2.7 Robotics -- 12.3 Conclusion -- References.
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| Record Nr. | UNINA-9910755076703321 |
Info
Advances in Applied Logics : Applications of Logic for Philosophy, Mathematics and Information Technology
