6 ms·

Yahtzee is 100% random luck from dice rolls. You can't "solve" it.

sram1337 1y ago
What do you think the link is about then?
AStonesThrow 1y ago
So I handed him my bottle, And he drank down my last swallow Then he bummed a cigarette, And asked me for a light And the night got deathly quiet And his face lost all expression... “If you’re gonna play the game, boy, Gotta learn to play it right.”
xyst 1y ago
skill issue
- bdhcuidbebe 1y ago
  Friendly reminder, this is orange site not red site
nkrisc 1y ago
The rolls may be random, and luck is a significant factor, but the game as a whole is not 100% random luck. You still have to make decisions. I do agree that “solve” isn’t the right word. Probably more accurate to refer to an optimal strategy.
cbarrick 1y ago
You should read more about Markov Decision Processes (MDPs) and Game Theory in general. The word "solve" is well defined in this context, and is used accurately by OP. You "solve" a game by finding the policy that maximizes the expected return. Obviously we can only talk about "expectation" because the outcome is random. But that doesn't mean that an optimal policy doesn't exist. Optimal policies are also often random, expressed like "in state S, perform action A with probability P and action B with probability 1-P". A policy then boils down to a table, with a row for each state and a column for each action, where each cell is the probability of performing that action in that state. Even more interesting are partially observable Markov decision processes, where your agent doesn't even know what state it is in. Instead, you get observations that hint to the true state, and you model the state as a probability distribution over possible concrete states. Solving these POMDPs is quite a bit more difficult than traditional MDPs. It is possible to solve some MDPs (and POMDPs) by hand, but in practice we often use reinforcement learning to learn the policy table by simulating games.
mathgeek 1y ago
You're wrong about it being 100% luck (you have choices that alter the outcomes). You're correct that the game cannot be solved by the definition of a solved game (being one where the outcome can be predicted from any position if both players play perfectly). https://en.wikipedia.org/wiki/Solved_game https://en.wikipedia.org/wiki/Solved_game

What do you think the link is about then?

So I handed him my bottle, And he drank down my last swallow Then he bummed a cigarette, And asked me for a light And the night got deathly quiet And his face lost all expression... “If you’re gonna play the game, boy, Gotta learn to play it right.”

xyst 1y ago

skill issue

bdhcuidbebe 1y ago
Friendly reminder, this is orange site not red site

nkrisc 1y ago

The rolls may be random, and luck is a significant factor, but the game as a whole is not 100% random luck. You still have to make decisions. I do agree that “solve” isn’t the right word. Probably more accurate to refer to an optimal strategy.

cbarrick 1y ago

You should read more about Markov Decision Processes (MDPs) and Game Theory in general. The word "solve" is well defined in this context, and is used accurately by OP. You "solve" a game by finding the policy that maximizes the expected return. Obviously we can only talk about "expectation" because the outcome is random. But that doesn't mean that an optimal policy doesn't exist. Optimal policies are also often random, expressed like "in state S, perform action A with probability P and action B with probability 1-P". A policy then boils down to a table, with a row for each state and a column for each action, where each cell is the probability of performing that action in that state. Even more interesting are partially observable Markov decision processes, where your agent doesn't even know what state it is in. Instead, you get observations that hint to the true state, and you model the state as a probability distribution over possible concrete states. Solving these POMDPs is quite a bit more difficult than traditional MDPs. It is possible to solve some MDPs (and POMDPs) by hand, but in practice we often use reinforcement learning to learn the policy table by simulating games.

mathgeek 1y ago

You're wrong about it being 100% luck (you have choices that alter the outcomes). You're correct that the game cannot be solved by the definition of a solved game (being one where the outcome can be predicted from any position if both players play perfectly). https://en.wikipedia.org/wiki/Solved_game https://en.wikipedia.org/wiki/Solved_game