Computational model of learning
Radford, Timothy John
The program described learns to improve its performance in the playing of a game, from experience. The main objectives of the project are that the system should observe the following principles: 1) The program should not rely on any special evaluation functions, which would embody domain-specific information. 2) Initial knowledge of the domain should be minimal, and further knowledge gained should be assimilated in terms of prior knowledge 3) The system of representation employed should as far as possible be independent of the domain, again avoiding the incorporation of domain-specific information. In customary Artificial Intelligence terms, the program is referred to as existing in a domain or environment. The model has a goal within this domain and has available certain actions which it may take in order to achieve its goal. The goal is represented as a Structure. This term will be used throughout to denote a set of objects from the domain, constrained by various domain-pertinent relationships. The actions, goals and objects are the initial known facts of the environment. The program has an innate ability to plan simple sequences of actions to achieve its goals. Inevitably, these plans do not take into account enough of the nature of the domain and prove inadequate. In such events the descriptive abilities of the program are invoked to correct the deficiency, and the program's model of its environment is enriched.