What is Knowledge-Based AI? – Georgia Tech – KBAI: Part1


Let us look at the processes that Watson may be using a little bit more closely. Clearly Watson is doing a large number of things. It is trying to understand natural language sentences. It is trying to generate some natural language sentences. It is making some decisions. I’ll group all of these things broadly under reasoning. Reasoning is a fundamental process of knowledge based data. A second fundamental process of knowledge based AIs learning. What simply is learning also? It perhaps gets a right answer to some questions, and stores that answer somewhere. If it gets a wrong answer, and then once it learns about the right answer, it stores the right answer also somewhere. Learning to is a fundamental process of knowledge based AI. A third fundamental process of knowledge based ai is memory. If you’re going to learn something, that knowledge that you’re learning has to be store somewhere, in memory. If you’re going to reason using knowledge, then that knowledge has to accessed from somewhere, from memory. From memory process it will store, what we learn as well as provide access to knowledge it will need for reasoning. These three forms of processes of learning, memory, and reasoning are intimately connected. We learn, so that we can reason. The result of reasoning often. Result in additional learning. Once we learn, we can store it in memory. However, we need knowledge to learn. The more we know, the more we can learn. Reasoning requires knowledge that memory can provide access to. The results of reasoning can also go into memory. So, here are three processes that are closely related. A key aspect of this course on knowledge based AI is that we will be talking about theories of knowledge based AI that unify reasoning, learning, and memory. And sort of, discussing any one of the three separately as sometimes happens in some schools of AI. We’re going to try to build, unify the concept. These 3 processes put together, I will call them deliberation. This deliberation process is 1 part of the overall architecture of a knowledge based AI agent. This figure illustrates the older architecture of an AI agent. Here we have input in the form of perceptions of the world. And output in the form of actions in the world. The agent may have large number of processes that map these perceptions to actions. We are going to focus right now on deliberation, but the agent architecture also includes metacognition and reaction, that we’ll discuss later

Leave a Reply