foundations of computational agents
Online, the information about the particular situation becomes available, and the agent has to act. The information includes the observations of the domain and often the preferences or goals. The agent can get observations from sensors, users, and other information sources, such as websites, although it typically does not have access to the domain experts or knowledge engineer while acting.
An agent typically has much more time for offline computation than for online computation. During online computation it can take advantage of particular goals and particular observations.
For example, a medical diagnosis system only has the details of a particular patient online. Offline, it can acquire knowledge about how diseases and symptoms interact and do some debugging and compilation. It can only do the computation about a particular patient online.
Online the following roles are involved:
A user is a person who has a need for expertise or has information about individual situations. Users typically are not experts in the domain of the knowledge base. They often do not know what information is needed by the system. Thus, it is unreasonable to expect them to volunteer everything that is true about a particular situation. A simple and natural interface must be provided because users do not typically understand the internal structure of the system. Users often, however, must make informed decisions based on the recommendation of the system; thus, they require an explanation of why the recommendation is appropriate.
Sensors provide information about the environment. For example, a thermometer is a sensor that can provide the current temperature at the location of the thermometer. Sensors may be more sophisticated, such as a vision sensor. At the lowest level, a vision sensor may simply provide an array of pixels at 50 frames per second. At a higher level, a vision system may be able to answer specific questions about the location of particular features, whether some type of individual is in the environment, or whether some particular individual is in the scene. An array of microphones can be used at a low level of abstraction to detect a sound of a particular frequency. Such an array may also be used as a component a speech understanding system.
Sensors come in two main varieties. A passive sensor continuously feeds information to the agent. Passive sensors include thermometers, cameras, and microphones. The designer can typically choose where the sensors are or where they are pointing, but they just feed the agent information. In contrast, an active sensor is controlled or queried for information. Examples of an active sensor include a medical probe able to answer specific questions about a patient or a test given to a student in an intelligent tutoring system. Often sensors that are passive sensors at lower levels of abstraction can be seen as active sensors at higher levels of abstraction. For example, a camera could be asked whether a particular person is in the room. To do this it may need to zoom in on the faces in the room, looking for distinguishing features of the person.
An external knowledge source, such as a website or a database, might be asked questions and can provide the answer for a limited domain. An agent can ask a weather website for the temperature at a particular location or an airline website for the arrival time of a particular flight. The knowledge sources have various protocols and efficiency trade-offs. The interface between an agent and an external knowledge source is called a wrapper. A wrapper translates between the representation the agent uses and the queries the external knowledge source is prepared to handle. Often wrappers are designed so that the agent is able to ask the same query of multiple knowledge sources. For example, an agent may want to know about airplane arrivals, but different airlines or airports may require very different protocols to access that information. When websites and databases adhere to a common ontology, they can be used together because the same symbols have the same meaning. Having the same symbols mean the same thing is called semantic interoperability. When they use different ontologies, there must be mappings between the ontologies to allow them to interoperate.