What Are Goal Based Reflex AI Agents?
Goal based AI agents simply use information that is part of their environment to achieve goals speciic to the goals programmed for the AI agent. These types of agents use search algorithms to help them find the best path to their desired outcomes and objective within a given environment. Sounds kind of tricky doesn't it? Actually goal based AI agents are rule based agents and great at sticking to their rules to achieve a given outcome. Goal based AI agents are programmed to follow a predefined role to help them accomplish their goals as well as take actions based on a variety of preset conditions. Goal based agents are quite easy to design compared to other types of AI agents and are able to handle very complex tasks.
Unlike the other types of AI agents that are basic models, goal based AI agents are able to determine the best course within it's decision making structure that included functions that are action taking that all depend on their predefined or programmed goal it wishes to accomplish. This type of agent works to find the best plan of action within it's decision making structure. Goal based agents use search algorithms that can be quite complex to help them find the most efficient path towards their desired goal.
Goal based AI agents are the type of artificial intelligence agents that perfrom from a predefined working pattern. Goal based Ai agents use this working pattern that is divided within 5 steps to it's decision making.
1) Perception: The goal based AI agent perceives the environment by using sensors that may include other devices for input to collect information of the AI agents surroundings to help set a specific goal.
2) Reasoning: Goal based AI agents analyze information that it collects and helps it to decide the best course of action to help the agent achieve it's primary goal.
3) Action: After the first 2 stages, the goal based AI agent then begins to take action. Some examples of a goal based AI agent taking some sort of action may include moving or manipulating certain objects with it's environment.
4) Evaluation: Once these specific actions are taken, the goal based artificial intelligence agent then evaluates the progress towards it's goal and at this point, may adjust it's actions if needed.
5) Completion of Goal: This final stage is the goal being reached and the AI agent that is goal based simply stops working or will begin working on a new goal and starting this process all over again.
There are many advantages with this type of AI agent that is goal based. They are typically simple to implement as well as understand. Since they are goal based agents, they are very efficient at reaching their goals. With this efficiency, evaluating the performance of the agent can simply be avaluated by easily looking at the predefined goal. Goal based agents are great for AI that is definitely well suited for predefined environments that are structured. Goal based AI agents are good for working in enviroments that include gaming, robotics as well as autonomous vehicles. There are a few disadvantages of goal based AI agents as they are limited to a specific goal. These agents are unable to adapt to changing environments, since thei goal is specific to a certain process. If there are too many variables, they are unable to complete certain tasks and large knowledge of the domain is required to help it reach that predefined goal.