Just for now, understand that you should not confuse the maximization of Expected Reward with the actual accumulation of actual Reward in practice during a run. They are not the same thing, and that is because the environment is partially observed.
Even if YOU DID have maximum reward accumulation, you should not confuse that with actual effective performance in practice. And the defense of that statement cannot fit in these comment boxes! voila!
I never said anything about this being outside of mathematical description. (putting words in my mouth yet again!) I think you and I need to take up this conversation in private messages because I'm sick and tired of the character limit on these stupid comment boxes. I assure you I can explain all of this very clear to you in private messages.
@otonanoC And constraints on time, space, and other resources are somehow mathematically unexplainable? There are entire fields of study devoted to representing such problems in the most mathematically optimal way, and they do in fact promote successful actions; it's how people manage businesses and governments. How are instinctual behaviors and adaptations somehow outside mathematical (or algorithmic) description?
Except those two things are not essentially the same at all! In the real world there are problems of morphology. Certainly no one is going make the claim that your embodied AIXI agent will have the capacity to rebuild its own body continually. In the real world there are time restraints, limits on space, and limited resources. We should not confuse the mathematical optimality of these equations with successful action in the real physical world.
@otonanoC If your point that is not practical to implement such an AIXI in real world applications, then that is only a result of human failure to do so. Any sufficiently advanced set of reward functions and knowledge representations should be capable of managing its own measure of success. Your argument, if I am reading correctly, is that instinctual behavior and adaptation to niches are essential. This is true, but is essentially the same as prioritized reward functions and genetic algorithms.
So that there is no confusion between the two of us let me emphasize this again --> I am not in any shape or form claiming I have found a logical error in the proof of AIXI as a general RL agent. I would hope your replies would stop putting that in my mouth.
Having said that, it is the lingering, often unspoken claim that such an agent will be effective in practice that is the source of all my arguments in these comment boxes.
In saying **you could easily add** -- what you really meant to say there is that the mathematical argument of AIXI **is unaffected by** the addition of these complex reward functions.
The easiness or uneasiness of adding such things in an effective embodied agent is a completely different issue. So you did not really mean "easy" there. What you meant is that the argument is unaffected by these things.
This clever trick where we redefine all the words we are using ahead of time in order to ensure that our mathematical proofs will work out the way we intended -- this is a game I do not intend to play with you.
How can you say in one breath that human beings are the closest example to strong AI, and in the next breath ignore the fact that human beings are embodied animals in a narrow context of the physical world of the earth? Do you believe intelligence exists in the universe for no reason related to their environment in which it is found?
Why are putting "real world" and "practical" in scare quotes here? I am not and I have not argued with the mathematical proofs and mathematical arguments of AIXI. I find this very peculiar that you always expect there to be a human in the loop of this AIXI agent who gives the "definition of a problem". You have ignored the very salient points I have made about an agent in a real setting.
@GeekProdigyGuy
Just for now, understand that you should not confuse the maximization of Expected Reward with the actual accumulation of actual Reward in practice during a run. They are not the same thing, and that is because the environment is partially observed.
Even if YOU DID have maximum reward accumulation, you should not confuse that with actual effective performance in practice. And the defense of that statement cannot fit in these comment boxes! voila!
otonanoC 1 week ago
@GeekProdigyGuy
I never said anything about this being outside of mathematical description. (putting words in my mouth yet again!) I think you and I need to take up this conversation in private messages because I'm sick and tired of the character limit on these stupid comment boxes. I assure you I can explain all of this very clear to you in private messages.
otonanoC 1 week ago
@otonanoC And constraints on time, space, and other resources are somehow mathematically unexplainable? There are entire fields of study devoted to representing such problems in the most mathematically optimal way, and they do in fact promote successful actions; it's how people manage businesses and governments. How are instinctual behaviors and adaptations somehow outside mathematical (or algorithmic) description?
GeekProdigyGuy 3 weeks ago
@GeekProdigyGuy
Except those two things are not essentially the same at all! In the real world there are problems of morphology. Certainly no one is going make the claim that your embodied AIXI agent will have the capacity to rebuild its own body continually. In the real world there are time restraints, limits on space, and limited resources. We should not confuse the mathematical optimality of these equations with successful action in the real physical world.
otonanoC 3 weeks ago
@otonanoC If your point that is not practical to implement such an AIXI in real world applications, then that is only a result of human failure to do so. Any sufficiently advanced set of reward functions and knowledge representations should be capable of managing its own measure of success. Your argument, if I am reading correctly, is that instinctual behavior and adaptation to niches are essential. This is true, but is essentially the same as prioritized reward functions and genetic algorithms.
GeekProdigyGuy 3 weeks ago
@GeekProdigyGuy
So that there is no confusion between the two of us let me emphasize this again --> I am not in any shape or form claiming I have found a logical error in the proof of AIXI as a general RL agent. I would hope your replies would stop putting that in my mouth.
Having said that, it is the lingering, often unspoken claim that such an agent will be effective in practice that is the source of all my arguments in these comment boxes.
otonanoC 3 weeks ago
@otonanoC
In saying **you could easily add** -- what you really meant to say there is that the mathematical argument of AIXI **is unaffected by** the addition of these complex reward functions.
The easiness or uneasiness of adding such things in an effective embodied agent is a completely different issue. So you did not really mean "easy" there. What you meant is that the argument is unaffected by these things.
otonanoC 3 weeks ago
@GeekProdigyGuy
This clever trick where we redefine all the words we are using ahead of time in order to ensure that our mathematical proofs will work out the way we intended -- this is a game I do not intend to play with you.
otonanoC 3 weeks ago
@GeekProdigyGuy
How can you say in one breath that human beings are the closest example to strong AI, and in the next breath ignore the fact that human beings are embodied animals in a narrow context of the physical world of the earth? Do you believe intelligence exists in the universe for no reason related to their environment in which it is found?
otonanoC 3 weeks ago
@GeekProdigyGuy
Why are putting "real world" and "practical" in scare quotes here? I am not and I have not argued with the mathematical proofs and mathematical arguments of AIXI. I find this very peculiar that you always expect there to be a human in the loop of this AIXI agent who gives the "definition of a problem". You have ignored the very salient points I have made about an agent in a real setting.
otonanoC 3 weeks ago