Info
- Utilizzare la checkbox di selezione a fianco di ciascun documento per attivare le funzionalità di stampa, invio email, download nei formati disponibili del (i) record.
Foundations of decision-making agents [[electronic resource] ] : logic, probability and modality / / Subrata Das
| Foundations of decision-making agents [[electronic resource] ] : logic, probability and modality / / Subrata Das |
| Autore | Das Subrata Kumar |
| Pubbl/distr/stampa | Singapore ; ; Hackensack, NJ, : World Scientific |
| Descrizione fisica | 1 online resource (385 p.) |
| Disciplina | 006.33 |
| Soggetto topico |
Intelligent agents (Computer software)
Artificial intelligence - Computer programs |
| Soggetto genere / forma | Electronic books. |
| ISBN |
1-281-93816-5
9786611938161 981-277-984-1 |
| Formato | Materiale a stampa  |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | ch. 1. Modeling agent epistemic states: an informal overview. 1.1. Models of agent epistemic states. 1.2. Propositional epistemic model. 1.3. Probabilistic epistemic model. 1.4. Possible world epistemic model. 1.5. Comparisons of models. 1.6. P3 model for decision-making agents -- ch. 2. Mathematical preliminaries. 2.1. Usage of symbols. 2.2. Sets, relations, and functions. 2.3. Graphs and trees. 2.4. Probability. 2.5. Algorithmic complexity -- ch. 3. Classical logics for the propositional epistemic model. 3.1. Propositional logic. 3.2. First-order logic. 3.3. Theorem proving procedure. 3.4. Resolution theorem proving. 3.5. Refutation procedure. 3.6. Complexity analysis -- ch. 4. Logic programming. 4.1. The concept. 4.2. Program clauses and goals. 4.3. Program semantics. 4.4. Definite programs. 4.5. Normal programs. 4.6. Prolog. 4.7. Prolog systems. 4.8. Complexity analysis -- ch. 5. Logical rules for making decisions. 5.1. Evolution of rules. 5.2. Bayesian probability theory for handling uncertainty. 5.3. Dempster-Shafer theory for handling uncertainty. 5.4. Measuring consensus. 5.5. Combining sources of varying confidence. 5.6. Advantages and disadvantages of rule-based systems -- ch. 6. Bayesian belief networks. 6.1. Bayesian belief networks. 6.2. Conditional independence in belief networks. 6.3. Evidence, belief, and likelihood. 6.4. Prior probabilities in networks without evidence. 6.5. Belief revision. 6.6. Evidence propagation in polytrees. 6.7. Evidence propagation in directed acyclic graphs. 6.8. Complexity of inference algorithms. 6.9. Acquisition of probabilities. 6.10. Advantages and disadvantages of belief networks. 6.11. Belief network tools -- ch. 7. Influence diagrams for making decisions. 7.1. Expected utility theory and decision trees. 7.2. Influence diagrams. 7.3. Inferencing in influence diagrams. 7.4. Compilation of influence diagrams. 7.5. Inferencing in strong junction tress -- ch. 8. Modal logics for the possible world epistemic model. 8.1. Historical development of modal logics. 8.2. Systems of modal logic. 8.3. Deductions in modal systems. 8.4. Modality. 8.5. Decidability and matrix method. 8.6. Relationships among modal systems. 8.7. Possible world semantics. 8.8. Soundness and completeness results. 8.9. Complexity and decidability of modal systems. 8.10. Modal first-order logics. 8.11. Resolution in modal first-order logics. 8.12. Modal epistemic logics. 8.13. Logic of agents beliefs (LAB) -- ch. 9. Symbolic argumentation for decision-making. 9.1. Toulmin's model of argumentation. 9.2. Domino decision-making model for P3. 9.3. Knowledge representation syntax of P3. 9.4. Formalization of P3 via LAB. 9.5. Aggregation via Dempster-Shafer theory. 9.6. Aggregation via Bayesian belief networks. |
| Record Nr. | UNINA-9910453551803321 |
Das Subrata Kumar
|
||
| Singapore ; ; Hackensack, NJ, : World Scientific | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Foundations of decision-making agents [[electronic resource] ] : logic, probability and modality / / Subrata Das
| Foundations of decision-making agents [[electronic resource] ] : logic, probability and modality / / Subrata Das |
| Autore | Das Subrata Kumar |
| Pubbl/distr/stampa | Singapore ; ; Hackensack, NJ, : World Scientific |
| Descrizione fisica | 1 online resource (385 p.) |
| Disciplina | 006.33 |
| Soggetto topico |
Intelligent agents (Computer software)
Artificial intelligence - Computer programs |
| ISBN |
1-281-93816-5
9786611938161 981-277-984-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | ch. 1. Modeling agent epistemic states: an informal overview. 1.1. Models of agent epistemic states. 1.2. Propositional epistemic model. 1.3. Probabilistic epistemic model. 1.4. Possible world epistemic model. 1.5. Comparisons of models. 1.6. P3 model for decision-making agents -- ch. 2. Mathematical preliminaries. 2.1. Usage of symbols. 2.2. Sets, relations, and functions. 2.3. Graphs and trees. 2.4. Probability. 2.5. Algorithmic complexity -- ch. 3. Classical logics for the propositional epistemic model. 3.1. Propositional logic. 3.2. First-order logic. 3.3. Theorem proving procedure. 3.4. Resolution theorem proving. 3.5. Refutation procedure. 3.6. Complexity analysis -- ch. 4. Logic programming. 4.1. The concept. 4.2. Program clauses and goals. 4.3. Program semantics. 4.4. Definite programs. 4.5. Normal programs. 4.6. Prolog. 4.7. Prolog systems. 4.8. Complexity analysis -- ch. 5. Logical rules for making decisions. 5.1. Evolution of rules. 5.2. Bayesian probability theory for handling uncertainty. 5.3. Dempster-Shafer theory for handling uncertainty. 5.4. Measuring consensus. 5.5. Combining sources of varying confidence. 5.6. Advantages and disadvantages of rule-based systems -- ch. 6. Bayesian belief networks. 6.1. Bayesian belief networks. 6.2. Conditional independence in belief networks. 6.3. Evidence, belief, and likelihood. 6.4. Prior probabilities in networks without evidence. 6.5. Belief revision. 6.6. Evidence propagation in polytrees. 6.7. Evidence propagation in directed acyclic graphs. 6.8. Complexity of inference algorithms. 6.9. Acquisition of probabilities. 6.10. Advantages and disadvantages of belief networks. 6.11. Belief network tools -- ch. 7. Influence diagrams for making decisions. 7.1. Expected utility theory and decision trees. 7.2. Influence diagrams. 7.3. Inferencing in influence diagrams. 7.4. Compilation of influence diagrams. 7.5. Inferencing in strong junction tress -- ch. 8. Modal logics for the possible world epistemic model. 8.1. Historical development of modal logics. 8.2. Systems of modal logic. 8.3. Deductions in modal systems. 8.4. Modality. 8.5. Decidability and matrix method. 8.6. Relationships among modal systems. 8.7. Possible world semantics. 8.8. Soundness and completeness results. 8.9. Complexity and decidability of modal systems. 8.10. Modal first-order logics. 8.11. Resolution in modal first-order logics. 8.12. Modal epistemic logics. 8.13. Logic of agents beliefs (LAB) -- ch. 9. Symbolic argumentation for decision-making. 9.1. Toulmin's model of argumentation. 9.2. Domino decision-making model for P3. 9.3. Knowledge representation syntax of P3. 9.4. Formalization of P3 via LAB. 9.5. Aggregation via Dempster-Shafer theory. 9.6. Aggregation via Bayesian belief networks. |
| Record Nr. | UNINA-9910782274603321 |
|
Das Subrata Kumar
|
||
| Singapore ; ; Hackensack, NJ, : World Scientific | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
Foundations of decision-making agents [[electronic resource] ] : logic, probability and modality / / Subrata Das
| Foundations of decision-making agents [[electronic resource] ] : logic, probability and modality / / Subrata Das |
| Autore | Das Subrata Kumar |
| Pubbl/distr/stampa | Singapore ; ; Hackensack, NJ, : World Scientific |
| Descrizione fisica | 1 online resource (385 p.) |
| Disciplina | 006.33 |
| Soggetto topico |
Intelligent agents (Computer software)
Artificial intelligence - Computer programs |
| ISBN |
1-281-93816-5
9786611938161 981-277-984-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | ch. 1. Modeling agent epistemic states: an informal overview. 1.1. Models of agent epistemic states. 1.2. Propositional epistemic model. 1.3. Probabilistic epistemic model. 1.4. Possible world epistemic model. 1.5. Comparisons of models. 1.6. P3 model for decision-making agents -- ch. 2. Mathematical preliminaries. 2.1. Usage of symbols. 2.2. Sets, relations, and functions. 2.3. Graphs and trees. 2.4. Probability. 2.5. Algorithmic complexity -- ch. 3. Classical logics for the propositional epistemic model. 3.1. Propositional logic. 3.2. First-order logic. 3.3. Theorem proving procedure. 3.4. Resolution theorem proving. 3.5. Refutation procedure. 3.6. Complexity analysis -- ch. 4. Logic programming. 4.1. The concept. 4.2. Program clauses and goals. 4.3. Program semantics. 4.4. Definite programs. 4.5. Normal programs. 4.6. Prolog. 4.7. Prolog systems. 4.8. Complexity analysis -- ch. 5. Logical rules for making decisions. 5.1. Evolution of rules. 5.2. Bayesian probability theory for handling uncertainty. 5.3. Dempster-Shafer theory for handling uncertainty. 5.4. Measuring consensus. 5.5. Combining sources of varying confidence. 5.6. Advantages and disadvantages of rule-based systems -- ch. 6. Bayesian belief networks. 6.1. Bayesian belief networks. 6.2. Conditional independence in belief networks. 6.3. Evidence, belief, and likelihood. 6.4. Prior probabilities in networks without evidence. 6.5. Belief revision. 6.6. Evidence propagation in polytrees. 6.7. Evidence propagation in directed acyclic graphs. 6.8. Complexity of inference algorithms. 6.9. Acquisition of probabilities. 6.10. Advantages and disadvantages of belief networks. 6.11. Belief network tools -- ch. 7. Influence diagrams for making decisions. 7.1. Expected utility theory and decision trees. 7.2. Influence diagrams. 7.3. Inferencing in influence diagrams. 7.4. Compilation of influence diagrams. 7.5. Inferencing in strong junction tress -- ch. 8. Modal logics for the possible world epistemic model. 8.1. Historical development of modal logics. 8.2. Systems of modal logic. 8.3. Deductions in modal systems. 8.4. Modality. 8.5. Decidability and matrix method. 8.6. Relationships among modal systems. 8.7. Possible world semantics. 8.8. Soundness and completeness results. 8.9. Complexity and decidability of modal systems. 8.10. Modal first-order logics. 8.11. Resolution in modal first-order logics. 8.12. Modal epistemic logics. 8.13. Logic of agents beliefs (LAB) -- ch. 9. Symbolic argumentation for decision-making. 9.1. Toulmin's model of argumentation. 9.2. Domino decision-making model for P3. 9.3. Knowledge representation syntax of P3. 9.4. Formalization of P3 via LAB. 9.5. Aggregation via Dempster-Shafer theory. 9.6. Aggregation via Bayesian belief networks. |
| Record Nr. | UNINA-9910825819003321 |
|
Das Subrata Kumar
|
||
| Singapore ; ; Hackensack, NJ, : World Scientific | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
High-level data fusion / / Subrata Das
| High-level data fusion / / Subrata Das |
| Autore | Das Subrata Kumar |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2008 |
| Descrizione fisica | 1 online resource (393 p.) |
| Disciplina | 004.01/9 |
| Soggetto topico |
Expert systems (Computer science)
Computational intelligence Human-machine systems Human-computer interaction |
| Soggetto genere / forma | Electronic books. |
| ISBN | 1-59693-282-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Models, architectures, and data -- Mathematical preliminaries -- Approaches to handling uncertainty -- Introduction to target tracking -- Target classification and aggregation -- Model-based situation assessment -- Modeling time for situation assessment -- Handling nonlinear and hybrid models -- Decision support -- Learning of fusion models -- Towards cognitive agents for data fusion -- Distributed fusion. |
| Record Nr. | UNINA-9910455135503321 |
|
Das Subrata Kumar
|
||
| Boston : , : Artech House, , ©2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
High-level data fusion / / Subrata Das
| High-level data fusion / / Subrata Das |
| Autore | Das Subrata Kumar |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2008 |
| Descrizione fisica | 1 online resource (393 p.) |
| Disciplina | 004.01/9 |
| Soggetto topico |
Expert systems (Computer science)
Computational intelligence Human-machine systems Human-computer interaction |
| ISBN | 1-59693-282-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Models, architectures, and data -- Mathematical preliminaries -- Approaches to handling uncertainty -- Introduction to target tracking -- Target classification and aggregation -- Model-based situation assessment -- Modeling time for situation assessment -- Handling nonlinear and hybrid models -- Decision support -- Learning of fusion models -- Towards cognitive agents for data fusion -- Distributed fusion. |
| Record Nr. | UNINA-9910778314503321 |
|
Das Subrata Kumar
|
||
| Boston : , : Artech House, , ©2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||
High-level data fusion / / Subrata Das
| High-level data fusion / / Subrata Das |
| Autore | Das Subrata Kumar |
| Pubbl/distr/stampa | Boston : , : Artech House, , ©2008 |
| Descrizione fisica | 1 online resource (393 p.) |
| Disciplina | 004.01/9 |
| Soggetto topico |
Expert systems (Computer science)
Computational intelligence Human-machine systems Human-computer interaction |
| ISBN | 1-59693-282-1 |
| Formato | Materiale a stampa |
| Livello bibliografico | Monografia |
| Lingua di pubblicazione | eng |
| Nota di contenuto | Models, architectures, and data -- Mathematical preliminaries -- Approaches to handling uncertainty -- Introduction to target tracking -- Target classification and aggregation -- Model-based situation assessment -- Modeling time for situation assessment -- Handling nonlinear and hybrid models -- Decision support -- Learning of fusion models -- Towards cognitive agents for data fusion -- Distributed fusion. |
| Record Nr. | UNINA-9910827735803321 |
|
Das Subrata Kumar
|
||
| Boston : , : Artech House, , ©2008 | ||
| Materiale a stampa | ||
| Lo trovi qui: Univ. Federico II | ||
| ||