What is an Expert System

An expert system is a computer program designed to simulate the problem-solving behavior of a human who is an expert in a narrow domain or discipline.

An expert system is normally composed of a knowledge base (information, heuristics, etc.), inference engine (analyzes the knowledge base), and the end user interface (accepting inputs, generating outputs). The path that leads to the development of expert systems is different from that of conventional programming techniques. The concepts for expert system development come from the subject domain of artificial intelligence (AI), and require a departure from conventional computing practices and programming techniques. A conventional program consists of an algorithmic process to reach a specific result. An AI program is made up of a knowledge base and a procedure to infer an answer. Expert systems are capable of delivering quantitative information, much of which has been developed through basic and applied research (e.g. economic thresholds, crop development models, pest population models) as well as heuristics to interpret qualitatively derived values, or for use in lieu of quantitative information. Another feature is that these systems can address imprecise and incomplete data through the assignment of confidence values to inputs and conclusions.

One of the most powerful attributes of expert systems is the ability to explain reasoning. Since the system remembers its logical chain of reasoning, a user may ask for an explanation of a recommendation and the system will display the factors it considered in providing a particular recommendation. This attribute enhances user confidence in the recommendation and acceptance of the expert system.

The development of an electronic decision support system requires the combined efforts of specialists from many fields of agriculture, and must be developed with the cooperation of the growers who use them. Specialists tend to be trained in rather narrow domains and are best at solving problems within that domain. However, there is a growing realization that the complex problems faced by growers go beyond the abilities of individual specialists. Interdisciplinary teams of specialists must work in unison to formulate solutions to agricultural problems. Agriculture must be viewed as a system of interacting parts where the perturbation of one part affects many others.


In agriculture, expert systems are capable of integrating the perspectives of individual disciplines (e.g. plant pathology, entomology, horticulture, agricultural meteorology) into a framework that best addresses the type of ad hoc decision-making required of modern farmers. Expert systems can be one of the most useful tools for accomplishing the task of providing growers with the day-to-day, integrated decision support needed to grow their crops.

What is Dumping?

Dumping is a discrimination of markets using different prices. There are various types of dumping, but we will investigate the most problematic one: persistent dumping.

If a firm has a protected domesitc market, it will behave as a monopolist in the market, and a competitor in the world market. When it sells one more unit, it will compare MR from the domestic market and the world market, and choose the higher.

We show the domestic MR as MR [1] and the world market MR as MRW that is the same as the world price PW. [2]

Now MR > MRW up to the point G. [3] Therefore, it will sell Q4 units in the domestic market [4] with a price of P'd. [5]

After that point, it will sell the good in the world market up to the point F where MRW=MC. [6] Thus it exports Q2 - Q4.


Domestic consumer surplus:

  • Autarky APdB [1]
  • Free trade APWE [2]
  • Dumping AP'dH [3]

  • Domestic producer surplus:

  • Autarky CPdBI [4]
  • Free trade CPWF [5]
  • Dumping CP'dHK+KGF [6]

  • Compared to free trade, by dumping, the domestic net loss is HGE