What is problem solving agent in Artificial Intelligence?

Question

Could someone tell me what is the problem-solving agent in Artificial Intelligence?

Answer 1

Problem-solving agent in Artificial Intelligence is goal-based agents that focus on goals, is one embodiment of a group of algorithms, and techniques to solve a well-defined problem in the area of Artificial Intelligence. And these agents are different from reflex agents who just have to map states into actions and can’t map when storing and learning both are bigger. The different stages that Problem-solving agents perform, to arrive at a desired state or solution are:

1. Articulating or expressing the desired goal and the problem is tried upon, clearly.
2. Explore and examine
3. Find the solution from the various algorithms on the table.
4. The final step is Execution!

You would know more of these jargons of AI once you are well through into the domain. Considering the job prospects, just knowing a technology doesn’t have any impact on the interview, how well do you know? Are you well versed in the technology? And the work experience you have, things like these often matter. And for these, I would recommend you to enroll in and end-to-end AI course from Intellipaat to help. Also, I would like you to watch our YouTube video on Artificial Intelligence for Beginners to help you get a better understanding.

Answer 2

In artificial intelligence, a problem-solving agent is viewed as a structured and purpose-built form of a problem-solving entity that is able to choose and implement a series of actions in order to achieve a defined goal. Problem-solving agents perform in more complicated activities which usually involve formulating and/or selection, in contrast to reflex agents who merely act on the present input by a pattern of action to state. The usual working structure of inner processes in these types of agents includes performing goal-oriented actions in steps: first, ascertaining the goal and analysing the nature of the problem; second, identifying and analysing opportunities; third, determining effective strategies by means of search algorithms; and finally, reaching the selected solution. As such, these problem-solving agents are very useful in the AI domain as they can be taken as a problem-solving tool for a particular well-defined problem where the most applicable characteristics are learning and the ability to adapt in a bid to enhance the effectiveness.