Architecture
Soar is based on a production system, it uses explicit production rules to govern its behavior (these are roughly of the form "if... then...", as also used in expert systems). Problem solving can be roughly described as a search through a problem space (the collection of different states which can be reached by the system at a particular time) for a goal state (which represents the solution for the problem). This is implemented by searching for the states which bring the system gradually closer to its goal. Each move consists of a decision cycle which has an elaboration phase (in which a variety of different pieces of knowledge bearing the problem are brought to Soar's working memory) and a decision procedure (which weighs what was found on the previous phase and assigns preferences to ultimately decide the action to be taken). In addition to problem space search, however, Soar can be used to instantiate reasoning techniques such as reinforcement learning which do not require detailed internal models of the environment. In this way, Soar is flexible to behaving when varying amounts of task knowledge are available.
SOAR originally stood for State, Operator And Result, reflecting this representation of problem solving as the application of an operator to a state to get a result. According to the project FAQ, the Soar development community no longer regards Soar as an acronym so it is no longer spelled all in caps though it is still representative of the core of the implementation.
If the decision procedure just described is not able to determine a unique course of action, Soar may use different strategies, known as weak methods to solve the impasse. These methods are appropriate to situations in which knowledge is not abundant. Some examples are means-ends analysis (which may calculate the difference between each available option and the goal state) and a type of hill-climbing. When a solution is found by one of these methods, Soar uses a learning technique called chunking to transform the course of action taken into a new rule. The new rule can then be applied whenever Soar encounters the situation again (that is, there will no longer be an impasse).
ACT-R is another cognitive architecture by John R. Anderson that operates on similar principles. Other cognitive architectures are CHREST, CLARION, ICARUS, DUAL, and Psi.
Read more about this topic: Soar (cognitive Architecture)
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