A goal-based AI agent can be defined as an intelligent program that can make decisions based on previous experiences, knowledge, user input, and the desired goal. The goal-based agent distinguishes itself through its ability to find a solution according to the required output.
AI agents can be of different types based on their working mechanisms and prediction algorithms. These AI agents can improve their prediction accuracy over time given training data is provided and the algorithms are tested frequently. Goal-based agents are also a type of AI agent.
Types of AI agents are as follows:
Goal-based AI agents are an expansion of model-based AI agents. These AI agents can perform all the tasks that model-based AI agents can perform, i.e., these models work on the current perception of the environment that is collected via sensors and the knowledge gained via historical events that have occurred. These both are required for the correct functioning of a model-based AI agent and a goal-based AI agent, but the additional functioning requirement of this model is the expected output.
In goal-based agents, the user provides the input and knows the expected output; thus, it is an example of supervised learning. The model performs the actions while keeping the goal state in perspective. The whole technique of the goal-based agent to reach a goal or a final state is based on searching and planning. The AI agent searches and develops the methodology that provides the easiest and most convenient pathway to reach a goal state.
There are hundreds of real-life examples in which we can see the exact implementation of steps taken by a goal-based agent. For example, a group of friends plan to go on a road trip. They have learned from past experiences that cars are more comfortable and suitable for longer distances. They search for the shortest route; this search is carried out keeping the destination in mind.
Here, the destination is the goal. Search and planning is carried out while keeping the end goal in mind. Past experiences were used to take the initial step towards solving the problem.