Russel Said: *"Oh, I can figure out how to solve most specific problems. From an AGI point of view, however, that leaves the question of how those individual solutions are going to serve as sources of knowledge for a system, rather than separate specific programs. My answer is to build something that can reason about code, for which formal logic is a necessary ingredient. If you can figure out another way to do it, I'm all ears!"
*Well, there are at least two problems here. *1) How to gain initial knowledge 2) How to use knowledge to achieve goals once we have it. * *1) How to gain initial knowledge* Ah, this is something very cool that I've been working on lately. Pick a particular example of initial knowledge from the example below and we can trace how it is learned and how such learning mechanisms can be implemented. There are many, so I'm not going to try to list them. I thought it would also be more fun for you all to pick one and surprise me. *Let's start with a simple example of 2 (using knowledge we already have and learning more) : Creating a Hello World program* Note that many of the details in how the reasoning is done are left out because 1) they are yet to be determined in detail and 2) the email is long enough without them. *Initial Assumptions: * The agent has some initial knowledge about programs, where one might find information about programming. The agent might have a text book on it. The agent understands what a hello world program is supposed to do. So, what are we solving for if the agent has so many initial capabilities? We're trying to show how the agent reasons about what it already knows to achieve a goal. The goal is to create a program that says "hello world". The agent understands this by reasons about statements made in a textbook about the "hello world" example program. The agent has to plan its actions to achieve the intention "write a hello world program". The plan is not a complete step by step plan. It just tells the general direction to go. This is the rough to fine heuristic that human beings often use. From there, does mean's ends analysis, searches for and finds information that might be relevant to the situation at hand, and reasons about what they've done in the past that have help achieve parts of such a goal. The AGI knows that programs can be created through the visual studio's IDE, based on reading about programming in C# (the book he/she has). So, it realizes that it needs to achieve a subgoal of finding visual studio's IDE to use it. It knows it can do this by getting to the computer and clicking on the icon that it knows is associated with visual studio. The program comes up. So, then we ask ourselves "what's the next step?". Our brain has marked memories associated with creating programs. It has recorded the fact that we clicked on the file menu to create a new program and that this was part of the process in achieving the goal. So, our memory pulls this fact and executes the action because we have no reasons to not pursue the action in memory. So, to this we go to the file menu and click "create a new project". We also pull in relevant information, which says you have to do <this that and the other> also if we want to create a program. We pull in relevant info from what we read in the text book about what to be careful of and what has to be done, etc. What's next? We want to make the program print out "hello world". we recall that we can do this by using the command "Console.WriteLine("")". and we recall that the thing printed out was in between the parantheses like so: Console.WriteLine("something to print out"); So, we hypothesize that if replace what was printed out with "hello world" that it will work. so we try Console.WriteLine("hello world"). it works! hurray. toda. done. Yeah, I know. It's over simplified. But you can see the types of reasoning that are required to achieve such a task. Do this thought experiment on enough problems and generalize what it takes to achieve them (don't try to overgeneralize though!). DO NOT THROW OUT the requirements. You cannot throw out computer vision because you don't know how to implement it. Sensory perception is a requirement for AGI for many reasons. So, just make it an assumption in your design until you can work out the details. We'll do the same thought experiment on computer vision as well to see how it can be integrated with the whole system. For now though, we're just focusing on this simple programming task. * * ------------------------------------------- AGI Archives: https://www.listbox.com/member/archive/303/=now RSS Feed: https://www.listbox.com/member/archive/rss/303/8660244-d750797a Modify Your Subscription: https://www.listbox.com/member/?member_id=8660244&id_secret=8660244-6e7fb59c Powered by Listbox: http://www.listbox.com