SUMMARYThe production system has been used extensively in Artificial Intelligence systems due, possibly, to a lack of a prior procedural orientation towards the knowledge embedded within it. As a result, this paradigm is especially useful in modeling domains in which a strong procedural correlation of data would not naturally appear. The production system is therefore an appropriate tool for designing models of systems of independent processes whose interactions can be defined in terms of system state.We are interested in modeling continuous, concurrent processes for simulating robot activities, and present a description of a system which is capable of representing such processes as symbolic expressions within a production system database. This system implements a world model which acts as a continuous function of time, and a set of rules written in a language capable of specifying time-dependent properties of the model. In addition, rules may specify new rules, thus permitting processes to be mapped out over time as sequences of events.The methodology presented in this paper is an attempt to utilize the power of symbolic programming in a design for world modeling, and a characterization of the requirements for applying such systems to problem domains which contain a continuous parameter, such as time. We believe that the technique of embedding time used here is appropriate for expressing the dynamic evolution of these models.
Characterization of the indigenous goat production system in Asossa zone, Benishangul Gumuz region, Ethiopia
