Contents
- 18.1 Overview
- 18.2 Introduction -- Experts in the Loop
- 18.3 Expert Systems
- 18.3.1 Uses of Expert Systems
- 18.3.2 Architecture of an Expert System
- 18.3.3 Explanation Facility
- 18.3.4 Dialogue and UI Component
- 18.3.5 Examples of Four Expert Systems
- 18.3.5.1 Example 1: MYCIN
- 18.3.5.2 Example 2: PROSPECTOR
- 18.3.5.3 Example 3: DENDRAL
- 18.3.5.4 Example 4: XCON
- 18.3.6 Building an Expert System
- 18.3.7 Limitations of Expert Systems
- 18.4 Knowledge Acquisition
- 18.4.1 Knowledge Elicitation
- 18.4.1.1 Unstructured Interviews
- 18.4.1.2 Structured Interviews
- 18.4.1.3 Focused Discussions
- 18.4.1.4 Role Reversal
- 18.4.1.5 Think-aloud
- 18.4.2 Knowledge Representation
- 18.4.2.1 Expert System Shells
- 18.4.2.2 High-level Programming Languages
- 18.4.2.3 Ontologies
- 18.4.2.4 Selecting a Tool
- 18.5 Experts and Machine Learning
- 18.5.1 Knowledge Elicitation for ML
- 18.5.1.1 Acquiring Tacit Knowledge
- 18.5.1.2 Feature Selection
- 18.5.1.3 Expert Labelling
- 18.5.1.4 Iteration and Interaction
- 18.5.2 Algorithmic Choice, Validation and Explanation
- 18.6 Decision Support Systems
- 18.6.1 Visualisation
- 18.6.2 Data Management and Analysis
- 18.6.3 Visual Analytics
- 18.6.3.1 Visualisation in VA
- 18.6.3.2 Data Management and Analysis for VA
- 18.7 Stepping Back
- 18.7.1 Who Is It About?
- 18.7.2 Why Are We Doing It?
- 18.7.3 Wider Context
- 18.7.4 Cost--Benefit Balance
- 18.8 Summary
Glossary items referenced in this chapter
accuracy, automation bias, backward reasoning, Bayes Theorem, black-box machine learning, bootstrapping, certainty factors, chatbot, clustering, COMPAS, computer vision, concept learning, confidence rating, connectionist model, constraint satisfaction, constraints, cost–benefit, data reduction, decision support system, decision tree, declarative knowledge, deep neural network, DENDRAL, depth first search, dialogue, dialogue component, dialogue!mixed control, dialogue!system control, dialogue!user control, domain-independent knowledge, domain-specific knowledge, down-sampling, ECG , evidence-based medicine, expert knowledge, expert system, expert system shell, expert system!brittleness, expert system!hybrid, expert system!limitations, expert system!meta-knowledge, expert system!purpose, expert system!rule tracing, expert system!shell, expert system!verification, explainable AI, explanation component, extensional representation, false negative, false positive, forward reasoning, frame, generate and test, genetic algorithm, genetic programming, ground truth, heuristic evaluation function, high-level programming languages, human labelling, hybrid, hybrid AI, hybrid architecture, hybrid expert system, inductive learning, interactive visualisation, Jaccard similarity, knowledge acquisition, knowledge base, knowledge elicitation, knowledge elicitation!critiquing, knowledge elicitation!focused discussions, knowledge elicitation!post-task walkthrough, knowledge elicitation!role reversal, knowledge elicitation!seed questions, knowledge elicitation!structured interview, knowledge elicitation!teach-back interview, knowledge elicitation!think aloud, knowledge elicitation!twenty questions, knowledge elicitation!unstructured interview, knowledge engineer, knowledge representation, Licklider, J.C.R., Lisp, logic, logic rules, machine learning, MYCIN, natural language processing, network representation, network visualisation, neural network, ontology, ontology editors, OPS5, overfitting, OWL, parallel coordinates, pattern recognition, physical constraints, Poplog, precision, probability, production rules, production system, Prolog, PROSPECTOR, Protégé, Python, Query-by-Browsing, random forest, rapid serial visualisation, RDF, recall, ROC, rule induction, scrutability, search space, search strategies, semantic network, semi-supervised learning, SHRDLU, similarity measure, simulated annealing, SQL, sub-symbolic systems, sufficient reason, symbolic machine learning, symbolic regression, synergistic interaction, synthetic data, tacit knowledge, uncertainty, unconscious bias, unsupervised clustering, unsupervised learning, user interface, visual analytics, visualisation, XCON