An agent is anything that can perceive its environment through sensors and act upon that environment through actuators.
An intelligent agent is an autonomous entity that uses AI techniques to make decisions and take actions to achieve its goals.
Key Components:
- Sensors: Collect data from the environment (e.g., cameras, microphones).
- Actuators: Perform actions in the environment (e.g., motors, speakers).
- Decision-Making: The agent uses its knowledge and reasoning to decide the best action.
Structure of Intelligent Agents:
The structure of an intelligent agent consists of:
- Perception: The agent perceives the environment through sensors.
- Reasoning: The agent processes the perceived information to make decisions.
- Action: The agent performs actions using actuators to influence the environment.
Agent Program:
- The core logic that maps perceptions to actions.
- Example: A thermostat perceives temperature and decides whether to turn the heater on or off.
Properties of Intelligent Agents:
- Autonomy: The agent operates without direct human intervention.
- Reactivity: The agent responds to changes in the environment in a timely manner.
- Proactiveness: The agent takes initiative to achieve its goals.
- Adaptability: The agent learns and improves its performance over time.
- Social Ability: The agent interacts with other agents or humans (in multi-agent systems).
Configuration of Agents:
The configuration of an agent involves:
- Sensors: To perceive the environment.
- Actuators: To act on the environment.
- Agent Program: To process inputs and generate actions.
- Knowledge Base: To store information about the environment and goals.
PEAS Description of Agents:
PEAS stands for Performance, Environment, Actuators, Sensors.
It is a framework for defining the task environment of an agent:
- Performance Measure: Criteria for evaluating the agent’s success.
- Environment: The context in which the agent operates.
- Actuators: The tools the agent uses to act.
- Sensors: The tools the agent uses to perceive.
Example (Self-Driving Car):
- Performance: Safety, speed, fuel efficiency.
- Environment: Roads, traffic, weather.
- Actuators: Steering wheel, brakes, accelerator.
- Sensors: Cameras, radar, GPS.
PAGE Description of Agents:
The PAGE model (Percepts, Actions, Goals, Environment) is a framework used to describe how an AI agent interacts with its surroundings.
- It provides a structured way to define an agent’s behavior based on its inputs, outputs, objectives, and operational context.
It describes the agent’s interaction with its environment:
- Percepts: They are the inputs or data an agent receives from its environment using sensors.
- Actions: They are the outputs or responses an agent performs based on its percepts.
- Goals: Goals define what the agent is trying to achieve.
- Environment: The external context in which the agent operates.
