Building Knowledge-Based Systems for Natural Resource Management

1 AI and Natural Resource Management. - 1. 1 Natural Resources. - 1. 2 Resource Management. - 1. 3 Knowledge: A Historical Framework. - 1. 4 Artificial Intelligence. - 1. 5 Knowledge-Based Systems. - 1. 6 Some Potential Benefits of Knowledge-Based Systems. - 1. 7 Limitations of Knowledge-Based Systems. - 1. 8 Suitable Application Areas. - 1. 9 Summary. - 2 Knowledge-Based Systems: Representation and Search. - 2. 1 An Overview of KBS Organization. - 2. 2 The Knowledge Base and Knowledge Representation. - 2. 3 Working Memory. - 2. 4 Search: Inference and Control. - 2. 5 Knowledge-Based System Architectures. - 2. 6 Summary and Additional Readings. - 3 Other Knowledge System Components. - 3. 1 Explanation and Justification. - 3. 2 User Interface. - 3. 3 Learning Capabilities. - 3. 4 Interfacing to Conventional Programs and Data Files. - 3. 5 Inexact Reasoning and Uncertainty. - 3. 6 Summary and Additional Readings. - 4 Planning the Application. - 4. 1 Parallelism and Cycling in the Development Process. - 4. 2 Alternative Development Methods. - 4. 3 Problem Definition. - 4. 4 Summary. - 5 Knowledge Acquisition. - 5. 1 Knowledge Acquisition in Overview. - 5. 2 Surface Versus Deep Knowledge. - 5. 3 Knowledge Acquisition Strategies. - 5. 4 Creating a Domain Ontology. - 5. 5 Acquisition Methods. - 5. 6 Domain Ontology and Acquisition Methods. - 5. 7 Knowledge Acquisition Scenarios. - 5. 8 Knowledge Acquisition Guidelines. - 5. 9 Expert Biases and Eliciting Uncertain Knowledge. - 5. 10 Summary and Additional Readings. - 6 Designing the Application. - 6. 1 Application Design = Knowledge Model + Human Factors Model. - 6. 2 Pre-Implementation Topics. - 6. 3 Prototyping. - 6. 4 Summary. - 7 Programming Knowledge Systems in Prolog. - 7. 1 Why Prolog?. - 7. 2 Introduction to Prolog. - 7. 3 Summary and Additional Readings. - 8 An Initial Prototype Using Native PROLOG. - 8. 1 Knowledge-Based System Architecture. - 8. 2 The Domain Level. - 8. 3 The Tactical Control Level. - 8. 4 System Control Level. - 8. 5 Putting It All Together. - 8. 6 From Native Prolog to Meta-PROLOG Programming. - 8. 7 Summary. - 9 A PROLOG Toolkit Approach to Developing Forest Management Knowledge-Based Systems. - 9. 1 A KBS Toolkit. - 9. 2 DSSTOOLS System Architecture. - 9. 3 Domain Level. - 9. 4 Tactical Control Level. - 9. 5 System Control Level. - 9. 6 Summary. - 10 System Evaluation and Delivery. - 10. 1 System Evaluation. - 10. 2 Delivery. - 10. 3 Summary. - Appendix A Roots of Artificial Intelligence. - A. 1 A Definition of Artificial Intelligence. - A. 2 Dreams of Intelligent Artifacts. - A. 2. 1 Ancient Dreams. - A. 2. 2 Modern Nightmares. - A. 3 Realization. - A. 3. 1 Realize What?. - A. 3. 2 Mind as a Tool. - A. 4 Knowledge. - A. 4. 1 Group Knowledge. - A. 4. 2 Hierarchical Structure. - A. 4. 3 Chunks. - A. 4. 4 Representation of Chunks. - A. 4. 4. 1 Frames and Semantic Networks. - A. 4. 4. 2 State Space. - A. 4. 4. 3 Artificial Neural Networks. - A. 4. 4. 4 Rules. - A. 4. 4. 5 Threaded Chunks. - A. 5 Goals. - A. 6 Reaching the Goal. - A. 6. 1 Generate-and-Test. - A. 6. 2 Goal Reduction. - A. 6. 3 State-Space Search. - A. 6. 4 Genetic Algorithms and Emergent Behavior. - A. 7 Interfacing or Conversing with the Statue. - A. 8 Testing and Conclusion. - Biliography. Language: English