On 7/7/23, Undescribed Horrific Abuse, One Victim & Survivor of Many <[email protected]> wrote: > On 7/7/23, Undescribed Horrific Abuse, One Victim & Survivor of Many > <[email protected]> wrote: >> regarding focus on a tree rather than a prompt, we might imagine >> instead some form kf access or memory present in the system. a robot >> for example might travel near important information, or pursue a step >> toward a goal, or an agent might be in or not in a state where a goal >> is already partly met > > the tree is roughly the decision tree i think which i have > somewhat-mysterious-inhibition around. it can go different spots. > > for example if we are playing tictactoe and want to win, we might > consider all the different moves we might make. this list of moves > forms the second row of a tree of parts of the world being considered, > kinda maybe rooted in what is certainly known about the present moment > which has only one option. then for each of those move states we > consider other things such as what the other player might do, or how > judgements apply to the move based on things known … … at some point > in this considering we form judgement or find states where the game is > won or lost. > > regions or possibilities in the tree where the game is lost fail to > meet the goal of winning the game and consideration is no longer > proceeded there and the areas need no longer be held in memory, it’s > maybe important to remove them to ensure they are properly nonincluded > during furhter c9nsideration (like an assertion check), assuming they > can always be reconsidered to rebuild the same data > > meanwhile regions or possibilities where the game is won meet the goal > of winning the game. the tree can be considered a planning structure > for meeting this goal, finding a path from the present moment to the > goal, start8ng from the present moment for efficient information > access if there is time pressure > > i imagine it can also be quite useful to start in the middle > especially in large spaces, this might assume something is known about > usual ways of meeting the goal in the environment, or at the end if > more is known at the end, and it’s nice to imagine including all three > in some way, unsure. basically new information might crop up anywhere > i suppose. > > it’s interesting to think of probabilistic information on various > areas being summaries or guesses of hidden expansions in detail
something i eventually found nice success around here was writing a tree exploration algorithm capable of changing where it was in the tree as priorities of different branches changed during exploration. this was pretty inhibited for me! i wrote a couple and i had chatgpt write some and i feel much more comfortable with it now! took some years. i still don’t use other parts of tree structures unfortunately and kinda strangrly. i think i probably emgaged that part because i associated it both with data structures and with AI, so it had maybe double the inhibition for me. i thought it would open up trees more, but maybe implementing it more would also help … it feels more inhibited after writing this
