Intelligent Agents: Characteristics, Types, and Attributes

Understanding Agency and Intelligent Agents

An agent is a system that acts to produce certain effects on its environment. Agency refers to the functional and structural qualities of the agents themselves. Intelligent agents are adaptable to changing environments, learn from experience, and choose the right actions based on a finite process of displaying information. They exhibit goal-directed behavior to achieve their objectives.

Essential Features of Intelligent Agents

Intelligent agents possess several key features:

• Attitudes such as beliefs and intentions
• Ability to gain knowledge
• Problem-solving capabilities
• Awareness of the limits of their own knowledge and abilities
• Potential for originality
• Ability to generalize
• Ability to perceive and understand

Rationality in Intelligent Agents

The rationality of agents is determined by:

• The performance measure that defines the degree of satisfaction
• The agent's perceptions or history of perceptions, called the sequence of perceptions

Common Attributes of Intelligent Agents

Intelligent agents share several common attributes:

• Communication Skill Level: The ability to communicate effectively.
• Level of Knowledge: The extent of their knowledge base.
• Mobility: The ability to migrate from the platform.
• Personality: The ability to exhibit attributes of credible human behavior.
• Reactivity: The ability to perceive and act selectively.
• Communication Time: Persistent identity and state over long periods.
• Adaptation: The ability to learn and improve with experience.
• Autonomy: Guided by objectives.
• Collaborative Behavior: The ability to work with other agents to achieve a common goal.
• Inference Capability: The ability to act with abstract specifications.

Classification of Intelligent Agents

Agents can be classified based on their attributes, exhibiting either a weak or strong notion of agency:

• Weak Agency: Originating from Distributed Computing (DC) and Distributed Artificial Intelligence (DAI), this view sees agents as a paradigm of an automatic network-based cooperative.
• Strong Agency: Stemming from artificial intelligence, this anthropomorphic vision portrays agents as having sensations, perceptions, and emotions similar to humans.

Distinguishing Between Agents and Objects

The primary difference between agents and objects lies in their degree of autonomy. Agents are not merely method invocations; they are autonomous entities that decide whether to act upon a request. In object-oriented systems, the decision to invoke a method rests with the invoking object. In contrast, with agents, the decision lies with the agent receiving the request. This highlights the concept of autonomous and flexible behavior (reactive, proactive, social). Each agent has its own control flow, whereas standard object models have a single control flow for the entire system.

Classifying Agents Based on Behavior

Agents can be classified from different perspectives:

• Physical Standpoint: Predictions are based on characteristics and physical laws.
• Design Standpoint: Predictions are based on what the system is designed to do.
• Intentional Standpoint: Predictions are based on assumptions of rational agency (beliefs, intentions, desires, etc.).