Are passive or active agents more intelligent?
A passive agent is an agent that simply does its thing but does not interact with the environment.
An active agent is an agent that actively interact with the environment.
Given those two definitions, we expect the active agent to appear more intelligent because it behaves according to its environment and interacts with it. A passive agent may however also behave according to its environment, it just doesn't try to alter it.
Is an agent that never says anything necessarily dumb? Such agent could be hiding all the information of the world within itself, and could potentially solve any problem thrown at him, but it simply does not offer such answers because it doesn't interact with the world. The relationship between the agent and the world is one-sided, from the environment (on)to the agent. From the outside, the agent looks like an inanimate object that doesn't know anything nor can it do anything. But if you are able to peek inside, you can observe the most complex processes occurring. I would suggest that such agent is highly intelligent.
In the stock market, we say that an investor is active if they regularly manage their portfolio, while a passive investor is one that manages their portfolio less frequently, depends on indexes instead of individual stocks and prefer to rely on the trend of stocks to make a profit. Active management is often compared to passive management as a benchmark, that is to say, you should not get involved in active management if your strategy cannot beat a simpler passive strategy. It is often the case that we see active investors as being foolish and more likely to lose money than passive investors.
Is there a general characteristic of simple programs that are able to learn complex behaviors, such as neural network or RL-based algorithms that can be implemented in less than 100-250 lines?
I don't know yet.
This question has come after thinking about DNA as being the code of human beings. DNA is also part of other animals, even viruses. Organisms use nucleotides to store the programs that are necessary to their existence. DNA is used to produce proteins within the body that accomplish various functions such as regulating our body, controlling our mood, our attention, our hunger, etc.
This code has evolved since we were non-biological. From a large amount of randomness (chemical elements), nucleotides were formed, which then somehow led to the formation of DNA itself after a likely long process. If through randomness we moved from a chaotic world to one with order and structure, and where a chain of DNA could finally emerge, it would be interesting to investigate the process in further details to determine whether it could give us clues regarding the process of creating a program that could evolve the same way DNA did.
Cellular automaton are also interesting to study in that aspect. By defining a small set of rules, it is possible to generate and observe complex behaviors.
One common behavior of cells is that they reproduce. As such, I would expect a program that can learn complex behaviors to have some reproductive function. Reproduction is considered as one of the traits of an entity being alive. My idea here is that exploring how we were able to massively populate the Earth may provide us with ideas on how a bit of code learned to lengthen itself, by the same process increasing the size of its host as well as the complexity and variety of cells that compose it.
Will an AGI be superior to a large group of individuals (e.g., society or a company)?
An AGI may be a strong single-minded entity. Unlike societies and companies that are composed of numerous individuals with different values/beliefs/opinions (VBO), an AGI is expected to have a single set of clear, concise and non-contradicting VBO. An AGI should be able to explore all potential alternatives and reason about all the potential sets of VBO in order to determine the most coherent and appropriate set to hold.
Meanwhile, we as individuals hold VBO that are often inconsistent. As a group, we are heterogenous in our VBO which means that conflict will arise since some sets of VBO cannot coexist. Our biggest issue is that we are competitive by nature. People fight over resources if they are limited. Fighting leads to winners and losers. The winners may not be necessarily the individuals with the "best" set of VBO. The fact that the "fittest" VBO may end up as the winner instead of the "best" set of VBO sounds unlikely to lead us to produce the optimal solution to a desired goal.
(This assumes that there is a single "best" VBO set and not various VBOs sets in the heterarchy of VBOs.)
How can I organize all the webpages I never read?
- Delete articles you know you will never read
- Add articles you'd like to read one day in a system such as pocket
- Track when articles are added to your "must-read" list, after 1 year "graduate" them by deleting them from the list
- Estimate how long an article takes to read and how much value you expect it will bring you
- Use the ROI to order your reading list
The following method applies to content online as well as offline (magazine article, books).
The first, most important, and difficult strategy, is to simply let go of those articles. Most of the time, we keep certain things out of fear of missing out. We may also think that if at some point we have free time we'll go through them, however that never happens. We always try to find something new instead. This can be seen as a way for the mind to communicate that it doesn't think it would be worthwhile to spend its time reading this content so it's better not to and instead we should look for alternative content to read.
Once you've gotten rid of all those articles you decided you would never read you can add them to tracking systems such as pocket. The idea here is that it may be possible for you to read this content, but in other contexts than when you're in front of your computer. Maybe you'd be likelier to read the article if you're waiting in line or waiting for your bus/subway. Maybe you'd read it if you're on your way to work.
Track when you add articles to your list. The older an article becomes, the less likely you will be to read it. As articles reach a certain age, it might be time to graduate them to the graveyard, in other words, to never read them. Mark them as read or remove them from your reading list.
You should have an idea of how long an article takes to read. Pocket offers an estimate of how long it takes to read an article. Knowing how long it takes to read an article is important since one of the techniques to get rid of articles is to go through all the short articles first since the time investment may be low.
As in the case of task management, the strategy we will want to adopt to organize and prioritize our reading will be related to the return on investment (ROI) metric. Each article should have an estimate of the value it will bring you to read it (e.g., how much you would have paid to acquire this knowledge), as well as an estimate of the effort (duration, e.g., how long it takes to read the article according to pocket) necessary to go through it. You can then order your reading list from articles with the highest ROI to the least ROI and feel more confident that you are reading high (expected) value content.
How can I easily identify the next book I should read when I have over 500 to choose from?
- Pick highly read books
- Determine why you want to read, this will filter out many books from your list
- Track how long you've wanted to read a book, you're more likely to read ones you recently added to your list
- Fiction: pick based on your tastes of the moment
- Non-fiction/technical: select a few books on the same topic, skim through them, then pick the best
My first heuristic when deciding which book to read is to consider how many people have already read it by using a site such as goodreads. The reason is that I want to read books that I may be able to discuss with others who will also have read the book. Reading niche books might be interesting, but it makes discussing them a lot more difficult.
For fiction books, I read books from a collection I've enjoyed at least one book. You could basically consider it book "social" proofing. For new books that are not part of a collection and from authors I've never read, I mostly decide based on my interests of the moment.
For non-fiction/technical books, I skim through a few books on the same topic and determine which book I feel the most confident will provide me with the most information presented in the most appropriate and succinct way.
Determining why you want to read will help you figure out what the most appropriate next book might be. You may want to relax and thus reading a technical book may not be appropriate while a fiction book would be. You may want to learn a new programming language and thus reading about a programming language you already know will not achieve that goal.
I suggest using a book tracker like goodreads as it will allow you to track when you added a book to your list. This will let you know how long the book has been sitting in your reading list, waiting to be read. Generally, the longer a book stays "shelved" the less likely it is you will ever read it. This generalizes to stating that most books are read in a LIFO (last in, first out) fashion.