Agent

An agent is “a system situated within and a part of an environment that senses that
environment and acts on it, over time, in pursuit of its own agenda and so as to affect
what it senses in the future.” (Franklin and Graesser 1997). It is a self-directed object, i.e. it has the ability to satisfy internal goals or objectives through actions and decisions based on a set of internal rules or strategies.” (Iglesias et al. 1999)

Types of agent

Characterstics of agent

• An agent is autonomous and self-directed. An agent can function independently in its environment and in its interac-tions with other agents, generally from a limited range of situations that are of interest. We refer to an agent’s beha-vior as the representation of a process that links the agent’s sensing of its environment to its decisions and actions.
• Agents are modular or self-contained. An agent is an identifiable, discrete individual with a set of characteristics or attributes, behaviors, and decision-making capability. The discreteness requirement implies that an agent has a boundary in a sense and one can easily determine whether something (that is, an element of the model’s state) is part of an agent, is not part of an agent, or is a characteristic shared among agents.
• An agent is social, interacting with other agents. Agents have protocols or mechanisms that describe how they inte-ract with other agents, just as an agent has behaviors. Common agent interaction protocols include contention for space and collision avoidance; agent recognition; communication and information exchange; influence; and other domain-or application-specific mechanisms.

Agents often have additional properties, which may or may not be considered as defining properties or necessary for agency.

• An agent may live in an environment. Agents interact with their environment as well as with other agents. An agent is situated, in the sense that its behavior is situationally dependent, which means that its behavior is based on the current state of its interactions with other agents and with the environment.
• An agent may have explicit goals that drive its behavior. The goals are not necessarily objectives to maximize as much as criteria against which to assess the effectiveness of its decision and actions. This allows an agent to conti-nuously compare the outcomes of its behaviors to its goals and gives it a benchmark for possibly modifying it beha-vior.
  • An agent may have the ability to learn and adapt its behaviors based on its experiences. Individual learning and adaptation requires an agent to have memory, usually in the form of a dynamic agent attribute. (We contrast individ-ual adaptation with population adaptation. In population adaptation, the proportion of individuals within the popu-lation with certain attributes that better suit them to their environment increases over time. The individuals do not necessarily change their behavior or adapt.)
  • Agents often have resource attributes that indicate its current stock of one or more resources, e.g., energy, wealth, information. These information are fully taken from (Macal and North, 2009) conference paper.