Intelligence → Judgemental
Knowledge → Codifiable, endorsed with relevance and purpose
Information → Scattered facts, easily transferable
Data → Contextual, tacit, transfer needs learning

The property that is not typically considered a property of a good system for the representation of knowledge in a particular domain is "Presentation adequacy." Presentation adequacy refers to how well the system's knowledge representation can be presented and understood by humans. While it's important to have a representation that can be comprehended by humans, the primary properties often associated with a good knowledge representation system are: Inferential Adequacy: The system's ability to support reasoning and inference within the domain. It should be able to draw meaningful conclusions and make inferences based on the represented knowledge. Inferential Efficiency: How efficiently the system can perform reasoning and inference. A good system should allow for efficient processing and deduction of new knowledge from the existing representation. Acquisitional Efficiency: How efficiently the system can acquire or learn new knowledge and integrate it into the existing representation. This relates to the ease of updating and expanding the knowledge base. While presentation adequacy is important for human understanding, it's not traditionally considered one of the core properties of a knowledge representation system. Instead, it's often viewed as an interface or display issue, focusing on how well the representation can be communicated to users.

→ An intelligent agent (IA) is an autonomous entity which observes through sensors and acts upon an environment using actuators (i.e. it is an agent) and directs its activity towards achieving goals (i.e. it is "rational", as defined in economics).
→ Intelligent agents may also learn or use knowledge to achieve their goals. They may be very simple or very complex. A reflex machine, such as a thermostat, is considered an example of an intelligent agent.