Chapter 8 Artificial intelligence in economics and finance: A state of the art — 1994 : The real estate price and assets and liability analysis case

This chapter emphasizes specific contributions, advantages, and weaknesses of artificial intelligence (AI) techniques various purposes: (1) knowledge-based reasoning that applies heuristic knowledge to make policy search more robust, or to satisfy trading principles in a competitive economy, (2) machine learning to learn the behavior of economic agents, (3) decision rationalization in decision support systems, and case-based reasoning, and (4) integration of databases and knowledge bases via suitable knowledge representations. In the real world of economic analysis, AI approaches must be scalable and tunable to changing characteristics without having to change the underlying techniques or algorithms. In economic applications, better explanation-based interfaces are necessary between the user and the system. From the perspective of business, almost no AI research addresses economic competition theories, either with reference to game theory, or to disequilibrium theories. The strongest potential of some AI techniques lies in their data/information fusion capability, which is little explored. This holds especially for neural networks, case-based reasoning, and knowledge representation standards.