An agent is anything that can be viewed as perceiving its environment through sensors and acting upon that environment through actuators. we use the term percept to refer to the agent's perceptual inputs at any given instant. An agent's perceptual sequence is the complete history of everything the agent has ever perceived. In general, an agent's choice of action at any given instant can depend on the entire percept sequence observed to date. If we can sepcify the agent's choice of action for every possible percept sequence, then we have said more or less everything there is to say about the agent. Mathematically speaking, we say that an agent's behavior is described by the agent function that maps any given percept sequence to an action.
There are five basic kinds of agent program that embody the principles underlying almost all intelligent systems:
Simple reflex agents;
Model-based reflex agents;
Goal-based agents;
Utility-based agents;
and
Learning agents.
(1). The model of simple reflex agents
(2). The model of model-based reflex agents
(3). The model of goal-based agents
(4). The model of utility-based agents
(5). The model of learning agents
References:
Russell, S., & Norvig,
P. (2003). Artificial Intelligence: A
Modern Approach, 2nd ed. New Jersey: Prentice Hall.