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A* over a Bayesian Network. https://en.wikipedia.org/wiki/A_search_algorithm https://en.wikipedia.org/wiki/A_search_algorithm https://en.wikipedia.org/wiki/B

A* over a Bayesian Network. https://en.wikipedia.org/wiki/A*_search_algorithm https://en.wikipedia.org/wiki/A*_search_algorithm https://en.wikipedia.org/wiki/Bayesian_network https://en.wikipedia.org/wiki/Bayesian_network

krapht 8y ago
What would your admissable heuristic be?
- pas 8y ago
  Discover as much of the map as possible? Talk to as many NPCs as possible? Try to get as many different dialogues from NPCs as possible? (I assume that to get to the you won dialogue means you encounter more dialogues than if you cleverly lose.)
  - ziaddotcom 8y ago
    With the bayesian mesh you could arbitrarily apply heuristics over what otherwise looks pretty similar to a simple coordinate map. If you happen to die near a certain node you could add an ajacent node of "scary" or whatever. Reverse idea for nodes where you get free food and pokemon.
    - MereInterest 8y ago
      Do you have a link to any papers about bayesian meshes? This sounds like a really neat technique, but my google-fu is failing me.
    - pas 8y ago
      Sure, the heuristic function can be as complex as one wants, but what's a good heuristic? How can we formalize winning Pokemon? (Without getting too low level, so that ideally the same heuristic would work for other RPGs too.)
- ziaddotcom 8y ago
  I could go many ways with that but I guess it depends how much we assume about the a.i. However, although the card game came out after the video game, I actually have thought about this pokemon a.i. a fair amount and I think its fair to same that the video game is in many ways a visualization of a card game and the traversing of the map isn't as critical as it seems. We know that the video game can't be beat without collecting x amount of Pokemon, so my thoughts on which heuristic would be to start there before even worrying about the battle system. Consider how a game of starcraft works, is a pokemon battle system more advanced than starcraft a.i.? I don't think so but open to being convinced otherwise.
  - thrower123 8y ago
    The card game is orders of magnitude more complicated than the video game battles - all that they are is very vanilla JRPG combat with a couple layers of rock, paper, scissors mechanics. One could probably write a finite state machine that would win 95% of the time in a couple hours. On the grand scale, Pokemon is essentially unloseable, as you can never really paint yourself into a corner you can't get out of. I've seen stupid challenge playthroughs where more than half the game can be beaten with only a single Magikarp... There are only a handful of unique encounters. Pure bloody-minded grinding will always see you through.
    - ziaddotcom 8y ago
      For actual gameplay, I said A card game, not the card game. Had something like war in mind. Although, I see how that may have been confusing as I made the connection of the card game version in the sentence before.
- deleted 8y ago
  [deleted]
antidesitter 8y ago
> A* over a Bayesian Network. Can you elaborate? I’m familiar with both individually, but am not sure what you mean by doing pathfinding over a directed graphical model.

A* over a Bayesian Network. https://en.wikipedia.org/wiki/A*_search_algorithm https://en.wikipedia.org/wiki/A*_search_algorithm https://en.wikipedia.org/wiki/B

krapht 8y ago

What would your admissable heuristic be?

pas 8y ago
Discover as much of the map as possible? Talk to as many NPCs as possible? Try to get as many different dialogues from NPCs as possible? (I assume that to get to the you won dialogue means you encounter more dialogues than if you cleverly lose.)
- ziaddotcom 8y ago
  With the bayesian mesh you could arbitrarily apply heuristics over what otherwise looks pretty similar to a simple coordinate map. If you happen to die near a certain node you could add an ajacent node of "scary" or whatever. Reverse idea for nodes where you get free food and pokemon.
  - MereInterest 8y ago
    Do you have a link to any papers about bayesian meshes? This sounds like a really neat technique, but my google-fu is failing me.
  - pas 8y ago
    Sure, the heuristic function can be as complex as one wants, but what's a good heuristic? How can we formalize winning Pokemon? (Without getting too low level, so that ideally the same heuristic would work for other RPGs too.)
ziaddotcom 8y ago
I could go many ways with that but I guess it depends how much we assume about the a.i. However, although the card game came out after the video game, I actually have thought about this pokemon a.i. a fair amount and I think its fair to same that the video game is in many ways a visualization of a card game and the traversing of the map isn't as critical as it seems. We know that the video game can't be beat without collecting x amount of Pokemon, so my thoughts on which heuristic would be to start there before even worrying about the battle system. Consider how a game of starcraft works, is a pokemon battle system more advanced than starcraft a.i.? I don't think so but open to being convinced otherwise.
- thrower123 8y ago
  The card game is orders of magnitude more complicated than the video game battles - all that they are is very vanilla JRPG combat with a couple layers of rock, paper, scissors mechanics. One could probably write a finite state machine that would win 95% of the time in a couple hours. On the grand scale, Pokemon is essentially unloseable, as you can never really paint yourself into a corner you can't get out of. I've seen stupid challenge playthroughs where more than half the game can be beaten with only a single Magikarp... There are only a handful of unique encounters. Pure bloody-minded grinding will always see you through.
  - ziaddotcom 8y ago
    For actual gameplay, I said A card game, not the card game. Had something like war in mind. Although, I see how that may have been confusing as I made the connection of the card game version in the sentence before.
deleted 8y ago
[deleted]

antidesitter 8y ago

> A* over a Bayesian Network. Can you elaborate? I’m familiar with both individually, but am not sure what you mean by doing pathfinding over a directed graphical model.