A part of Artificial Intelligence works towards developing intelligent agents, which are used to automated some tasks via some sort of logical reasoning. These agents are able to perceive some information from the environment and take some action(s) based on those perceptions. The intelligent agents work towards finding the set of actions, which would lead them to a certain pre-determined goal. This type of agents are called as Perception-Action-Goal-Environment agents.
Search techniques are employed to map a set of perception into a single or a set of actions. The search techniques can be divided into uniform cost search or informed search. Heuristics are used in informed search methods to find an optimal set of actions to achieve the desired goals.
Knowledge representation methods are used to describe the relationships between different objects in the environment. Examples for these are First Order Logic and production rules. Some of these knowledge representation methods can also be used to describe the semantics of the knowledge, e.g. frames for semantic networks.
Knowledge acquisition, maintenance and application are other branches of Artificial Intelligence, which are highly related with Databases and also with Data Mining.