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4 Commits
89aba4f930
...
786e70fe9a
Author | SHA1 | Date |
---|---|---|
Mark | 786e70fe9a | |
Mark | 00270569db | |
Mark | b39c618a2a | |
Mark | 4ee7f8a9ac |
|
@ -120,6 +120,31 @@ version = "1.0.0"
|
|||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "acbf1af155f9b9ef647e42cdc158db4b64a1b61f743629225fde6f3e0be2a7c7"
|
||||
|
||||
[[package]]
|
||||
name = "crossbeam-deque"
|
||||
version = "0.8.5"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "613f8cc01fe9cf1a3eb3d7f488fd2fa8388403e97039e2f73692932e291a770d"
|
||||
dependencies = [
|
||||
"crossbeam-epoch",
|
||||
"crossbeam-utils",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "crossbeam-epoch"
|
||||
version = "0.9.18"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "5b82ac4a3c2ca9c3460964f020e1402edd5753411d7737aa39c3714ad1b5420e"
|
||||
dependencies = [
|
||||
"crossbeam-utils",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "crossbeam-utils"
|
||||
version = "0.8.19"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "248e3bacc7dc6baa3b21e405ee045c3047101a49145e7e9eca583ab4c2ca5345"
|
||||
|
||||
[[package]]
|
||||
name = "either"
|
||||
version = "1.10.0"
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||||
|
@ -177,6 +202,7 @@ dependencies = [
|
|||
"clap",
|
||||
"itertools",
|
||||
"rand",
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||||
"rayon",
|
||||
"termion",
|
||||
]
|
||||
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||||
|
@ -240,6 +266,26 @@ dependencies = [
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|||
"getrandom",
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||||
]
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||||
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||||
[[package]]
|
||||
name = "rayon"
|
||||
version = "1.9.0"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "e4963ed1bc86e4f3ee217022bd855b297cef07fb9eac5dfa1f788b220b49b3bd"
|
||||
dependencies = [
|
||||
"either",
|
||||
"rayon-core",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "rayon-core"
|
||||
version = "1.12.1"
|
||||
source = "registry+https://github.com/rust-lang/crates.io-index"
|
||||
checksum = "1465873a3dfdaa8ae7cb14b4383657caab0b3e8a0aa9ae8e04b044854c8dfce2"
|
||||
dependencies = [
|
||||
"crossbeam-deque",
|
||||
"crossbeam-utils",
|
||||
]
|
||||
|
||||
[[package]]
|
||||
name = "redox_syscall"
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||||
version = "0.4.1"
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|
|
|
@ -8,4 +8,5 @@ anyhow = "1.0.80"
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clap = { version = "4.5.1", features = ["derive"] }
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itertools = "0.12.1"
|
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rand = "0.8.5"
|
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rayon = "1.9.0"
|
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termion = "3.0.0"
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|
|
12
README.md
12
README.md
|
@ -22,7 +22,15 @@ As always, run this project with `cargo run`. The app takes one argument by defa
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- `random`: Play against a random agent (very easy)
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- `chase`: Play against a simple extremum-chasing agent (easy)
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- `diffuse`: Play against a slightly more intellegent extremum chaser (medium)
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- `brutus`: Play against a simple brute-force agent (hard)
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For example, `cargo run -- random` will play a game against a random player. Use your arrow keys and space bar to play the game.
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For example, `cargo run -- random` will start a game against a random player. Use your arrow keys and space bar to play.
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Additional options are available, see `cargo run -- --help`.
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Additional options are available, see `cargo run -- --help`.
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Win rates against random are as follows:
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- `human`: ~100%
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- `random`: ~50%
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- `chase`: ~70%
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- `diffuse`: ~76%
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- `brutus`: ~90%
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|
@ -0,0 +1,142 @@
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use std::{cmp::Ordering, iter};
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use anyhow::Result;
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use itertools::Itertools;
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use rand::{seq::SliceRandom, thread_rng};
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use rayon::iter::{ParallelBridge, ParallelIterator};
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use super::{Agent, Chase, MaximizerAgent, MinimizerAgent};
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use crate::{
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agents::{util::best_board_noop, Diffuse},
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board::{Board, PlayerAction},
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util::{Player, Symb},
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};
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pub struct Brutus {
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player: Player,
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}
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impl Brutus {
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pub fn new(player: Player) -> Self {
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Self { player }
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}
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fn step(&mut self, board: &Board, minimize: bool) -> Result<PlayerAction> {
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let symbols = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div]
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.into_iter()
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.filter(|x| !board.contains(*x))
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.collect_vec();
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if symbols.is_empty() {
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return if minimize {
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Chase::new(self.player).step_min(board)
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} else {
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Chase::new(self.player).step_max(board)
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};
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}
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// Number of free slots
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let n_free = board.get_board().iter().filter(|x| x.is_none()).count();
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// Number of slots we need to fill with numbers
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// Add one if we have two or fewer symbols available, so that we can
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// account for one unused symbol while keeping a reasonable runtime
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let n_fill = n_free - symbols.len() + if symbols.len() <= 2 { 1 } else { 0 };
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let mut items = iter::repeat(None)
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.take(n_fill)
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.chain(symbols.iter().map(|x| Some(x.clone())))
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.permutations(n_free)
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.unique()
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.par_bridge()
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.filter_map(move |x| {
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let mut tmp_board = board.clone();
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for (i, s) in x.iter().enumerate() {
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if let Some(s) = s {
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let pos = board.ith_empty_slot(i).unwrap();
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if !tmp_board.can_play(&PlayerAction { symb: *s, pos }) {
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return None;
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}
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tmp_board.get_board_mut()[pos] = Some(*s);
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}
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}
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let min = best_board_noop(&tmp_board, true);
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let max = best_board_noop(&tmp_board, false);
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if min.is_none() || max.is_none() {
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return None;
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}
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let v_min = min.unwrap().evaluate().unwrap();
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let v_max = max.unwrap().evaluate().unwrap();
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let v = v_min + v_max / 2.0;
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Some((tmp_board, v))
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})
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.collect::<Vec<_>>();
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if minimize {
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// Sort from smallest to biggest midpoint
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items.sort_by(|a, b| a.1.partial_cmp(&b.1).unwrap_or(Ordering::Equal));
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} else {
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items.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(Ordering::Equal));
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}
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// TODO: why can `items` be empty?
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// We shouldn't need this escape hatch
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if items.is_empty() {
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return if minimize {
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Diffuse::new(self.player).step_min(board)
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} else {
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Diffuse::new(self.player).step_max(board)
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};
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}
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let (t, _) = items.first().unwrap();
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let mut symbols = symbols.clone();
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symbols.shuffle(&mut thread_rng());
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// Place a random unused symbol
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for target_s in symbols {
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for (i, s) in t.get_board().iter().enumerate() {
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if let Some(s) = s {
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if board.get_board()[i].is_none() && target_s == *s {
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return Ok(PlayerAction { pos: i, symb: *s });
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}
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}
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}
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}
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// Final escape hatch, if we didn't decide to place any symbols
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// (which is possible, since we add one to free_spots above!)
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if minimize {
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Chase::new(self.player).step_min(board)
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} else {
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Chase::new(self.player).step_max(board)
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}
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}
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}
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impl Agent for Brutus {
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fn name(&self) -> &'static str {
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"Brutus"
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}
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fn player(&self) -> Player {
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self.player
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}
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}
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impl MinimizerAgent for Brutus {
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fn step_min(&mut self, board: &Board) -> Result<PlayerAction> {
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self.step(board, true)
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}
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}
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impl MaximizerAgent for Brutus {
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fn step_max(&mut self, board: &Board) -> Result<PlayerAction> {
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self.step(board, false)
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}
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}
|
|
@ -1,4 +1,5 @@
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use anyhow::Result;
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use rand::{seq::SliceRandom, thread_rng};
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use super::{Agent, Chase, MaximizerAgent, MinimizerAgent, Random};
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use crate::{
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|
@ -9,6 +10,7 @@ use crate::{
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/// A simple "operator diffusion" MINIMIZER agent.
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///
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/// Tries to keep operators as far apart as possible, denying large numbers.
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/// Places numbers using the same algorithm as chase.
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pub struct Diffuse {
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player: Player,
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}
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|
@ -86,9 +88,9 @@ impl Agent for Diffuse {
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impl MinimizerAgent for Diffuse {
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fn step_min(&mut self, board: &Board) -> Result<PlayerAction> {
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let symb = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div]
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.iter()
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.find(|x| !board.contains(**x));
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let mut x = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div];
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x.shuffle(&mut thread_rng());
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let symb = x.iter().find(|x| !board.contains(**x));
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if let Some(symb) = symb {
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Ok(self.step_symb(board, *symb))
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|
@ -101,9 +103,9 @@ impl MinimizerAgent for Diffuse {
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impl MaximizerAgent for Diffuse {
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fn step_max(&mut self, board: &Board) -> Result<PlayerAction> {
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let symb = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div]
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.iter()
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.find(|x| !board.contains(**x));
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let mut x = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div];
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x.shuffle(&mut thread_rng());
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let symb = x.iter().find(|x| !board.contains(**x));
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if let Some(symb) = symb {
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Ok(self.step_symb(board, *symb))
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|
|
|
@ -195,7 +195,7 @@ impl Human {
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impl Agent for Human {
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fn name(&self) -> &'static str {
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"Player"
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"Human"
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}
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fn player(&self) -> Player {
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|
|
|
@ -1,9 +1,11 @@
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mod brutus;
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mod chase;
|
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mod diffuse;
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mod human;
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mod random;
|
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pub mod util;
|
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|
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pub use brutus::Brutus;
|
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pub use chase::Chase;
|
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pub use diffuse::Diffuse;
|
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pub use human::Human;
|
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|
|
|
@ -1,10 +1,10 @@
|
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use itertools::Itertools;
|
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use std::num::NonZeroU8;
|
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use std::{mem::swap, num::NonZeroU8};
|
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|
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use crate::{board::Board, util::Symb};
|
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|
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/// Returns an iterator of (sort, coords, char_idx, f32) for each empty slot in the listed partials.
|
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/// - sort is the index of this slot.
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/// Returns an iterator of (idx, coords, char_idx, f32) for each empty slot in the listed partials.
|
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/// - idx is the index of this slot in the board string.
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/// - coords are the coordinate of this slot's partial
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/// - char_idx is the index of this slot in its partial
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/// - f32 is the influence of this slot
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|
@ -51,16 +51,12 @@ pub fn free_slots_by_influence(board: &Board) -> Option<Vec<(usize, f32)>> {
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Some(slots)
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}
|
||||
|
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/// Find the maximum possible value of the given board
|
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#[allow(dead_code)]
|
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pub fn maximize_value(board: &Board) -> Option<Board> {
|
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/// Find the minimum or maximum possible value of the given board,
|
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/// without adding any operations. Returns None if we couldn't find
|
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/// a best board.
|
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pub fn best_board_noop(board: &Board, minimize: bool) -> Option<Board> {
|
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let n_free = board.get_board().iter().filter(|x| x.is_none()).count();
|
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|
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// Assume we have 10 or fewer available slots
|
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if n_free >= 10 {
|
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panic!()
|
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}
|
||||
|
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let available_numbers = (0..=9)
|
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.map(|x| match x {
|
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0 => Symb::Zero,
|
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|
@ -69,19 +65,36 @@ pub fn maximize_value(board: &Board) -> Option<Board> {
|
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.filter(|x| !board.contains(*x))
|
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.collect::<Vec<_>>();
|
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|
||||
if n_free > available_numbers.len() {
|
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return None;
|
||||
}
|
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|
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let slots = free_slots_by_influence(board)?;
|
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|
||||
let all_symbols = {
|
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// We need this many from the bottom, and this many from the top.
|
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let neg_count = slots.iter().filter(|(_, x)| *x <= 0.0).count();
|
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let pos_count = slots.iter().filter(|(_, x)| *x > 0.0).count();
|
||||
let mut a = {
|
||||
// Number of slots we want to minimize
|
||||
let mut neg_count = slots.iter().filter(|(_, x)| *x <= 0.0).count();
|
||||
// Number of slots we want to maximize
|
||||
let mut pos_count = slots.iter().filter(|(_, x)| *x > 0.0).count();
|
||||
|
||||
let mut a_iter = available_numbers
|
||||
.iter()
|
||||
.take(neg_count)
|
||||
.chain(available_numbers.iter().rev().take(pos_count).rev());
|
||||
if minimize {
|
||||
swap(&mut neg_count, &mut pos_count);
|
||||
}
|
||||
|
||||
let mut g = slots
|
||||
available_numbers
|
||||
.iter()
|
||||
.take(neg_count)
|
||||
.chain(available_numbers.iter().rev().take(pos_count).rev())
|
||||
.collect_vec()
|
||||
};
|
||||
|
||||
if !minimize {
|
||||
a.reverse();
|
||||
}
|
||||
let mut a_iter = a.into_iter();
|
||||
|
||||
slots
|
||||
// Group slots with equal weights
|
||||
// and count the number of elements in each group
|
||||
.iter()
|
||||
|
@ -101,37 +114,32 @@ pub fn maximize_value(board: &Board) -> Option<Board> {
|
|||
// of this set of sets
|
||||
.multi_cartesian_product()
|
||||
.map(|x| x.iter().flatten().cloned().collect_vec())
|
||||
.map(|v| slots.iter().zip(v).collect_vec())
|
||||
.collect_vec();
|
||||
|
||||
// Sort these vectors so the order of values
|
||||
// matches the order of empty slots
|
||||
g.iter_mut()
|
||||
.for_each(|v| v.sort_by(|(a, _), (b, _)| b.0.partial_cmp(&a.0).unwrap()));
|
||||
g.into_iter()
|
||||
.map(|v| v.into_iter().map(|(_, s)| s).collect_vec())
|
||||
// Finally, attach the coordinate of each slot to each symbol
|
||||
.map(|v| slots.iter().map(|x| x.0).zip(v).collect_vec())
|
||||
.collect_vec()
|
||||
};
|
||||
|
||||
let mut best_board = None;
|
||||
let mut best_value = None;
|
||||
for i in all_symbols {
|
||||
let mut i_iter = i.iter();
|
||||
let filled = Board::from_board(board.get_board().map(|x| match x {
|
||||
None => i_iter.next().cloned(),
|
||||
_ => x,
|
||||
}));
|
||||
for i_iter in all_symbols {
|
||||
let mut tmp_board = board.clone();
|
||||
for (i, s) in i_iter {
|
||||
tmp_board.get_board_mut()[i] = Some(s);
|
||||
}
|
||||
|
||||
let val = filled.evaluate();
|
||||
let val = tmp_board.evaluate();
|
||||
|
||||
if let Some(val) = val {
|
||||
if let Some(best) = best_value {
|
||||
if val > best {
|
||||
if minimize {
|
||||
if best_value.is_none() || val < best_value.unwrap() {
|
||||
best_value = Some(val);
|
||||
best_board = Some(filled)
|
||||
best_board = Some(tmp_board)
|
||||
}
|
||||
} else {
|
||||
best_value = Some(val);
|
||||
best_board = Some(filled)
|
||||
if best_value.is_none() || val > best_value.unwrap() {
|
||||
best_value = Some(val);
|
||||
best_board = Some(tmp_board)
|
||||
}
|
||||
}
|
||||
}
|
||||
}
|
||||
|
|
|
@ -1,6 +1,6 @@
|
|||
use anyhow::Result;
|
||||
use itertools::Itertools;
|
||||
use std::fmt::{Display, Write};
|
||||
use std::fmt::{Debug, Display, Write};
|
||||
use termion::color::{self, Color};
|
||||
|
||||
use super::{PlayerAction, TreeElement};
|
||||
|
@ -74,6 +74,12 @@ impl Display for Board {
|
|||
}
|
||||
}
|
||||
|
||||
impl Debug for Board {
|
||||
fn fmt(&self, f: &mut std::fmt::Formatter<'_>) -> std::fmt::Result {
|
||||
Display::fmt(&self, f)
|
||||
}
|
||||
}
|
||||
|
||||
#[allow(dead_code)]
|
||||
impl Board {
|
||||
pub fn new() -> Self {
|
||||
|
@ -93,6 +99,24 @@ impl Board {
|
|||
&mut self.board
|
||||
}
|
||||
|
||||
/// Get the index of the ith empty slot
|
||||
pub fn ith_empty_slot(&self, mut idx: usize) -> Option<usize> {
|
||||
for (i, c) in self.board.iter().enumerate() {
|
||||
if c.is_none() {
|
||||
if idx == 0 {
|
||||
return Some(i);
|
||||
}
|
||||
idx -= 1;
|
||||
}
|
||||
}
|
||||
|
||||
if idx == 0 {
|
||||
Some(self.board.len() - 1)
|
||||
} else {
|
||||
None
|
||||
}
|
||||
}
|
||||
|
||||
pub fn is_done(&self) -> bool {
|
||||
self.free_spots == 0
|
||||
}
|
||||
|
|
14
src/cli.rs
14
src/cli.rs
|
@ -3,7 +3,7 @@ use std::fmt::Display;
|
|||
use clap::{Parser, ValueEnum};
|
||||
|
||||
use crate::{
|
||||
agents::{Chase, Diffuse, Human, MaximizerAgent, MinimizerAgent, Random},
|
||||
agents::{Brutus, Chase, Diffuse, Human, MaximizerAgent, MinimizerAgent, Random},
|
||||
util::Player,
|
||||
};
|
||||
|
||||
|
@ -18,14 +18,8 @@ pub struct Cli {
|
|||
pub red: AgentSelector,
|
||||
|
||||
/// If this is greater than one, repeat the game this many times and print a summary.
|
||||
/// Best used with --silent.
|
||||
#[arg(long, short, default_value = "0")]
|
||||
pub repeat: usize,
|
||||
|
||||
/// If this is given, do not print boards.
|
||||
/// Good for bulk runs with --repeat, bad for human players.
|
||||
#[arg(long, short, default_value = "false")]
|
||||
pub silent: bool,
|
||||
}
|
||||
|
||||
#[derive(Debug, Copy, Clone, PartialEq, Eq, PartialOrd, Ord, ValueEnum)]
|
||||
|
@ -41,6 +35,9 @@ pub enum AgentSelector {
|
|||
|
||||
/// A smarter extremum-chaser (medium)
|
||||
Diffuse,
|
||||
|
||||
/// A very smart brute-force agent (hard)
|
||||
Brutus,
|
||||
}
|
||||
|
||||
impl AgentSelector {
|
||||
|
@ -49,6 +46,7 @@ impl AgentSelector {
|
|||
Self::Random => Box::new(Random::new(player)),
|
||||
Self::Chase => Box::new(Chase::new(player)),
|
||||
Self::Diffuse => Box::new(Diffuse::new(player)),
|
||||
Self::Brutus => Box::new(Brutus::new(player)),
|
||||
Self::Human => Box::new(Human::new(player)),
|
||||
}
|
||||
}
|
||||
|
@ -58,6 +56,7 @@ impl AgentSelector {
|
|||
Self::Random => Box::new(Random::new(player)),
|
||||
Self::Chase => Box::new(Chase::new(player)),
|
||||
Self::Diffuse => Box::new(Diffuse::new(player)),
|
||||
Self::Brutus => Box::new(Brutus::new(player)),
|
||||
Self::Human => Box::new(Human::new(player)),
|
||||
}
|
||||
}
|
||||
|
@ -71,6 +70,7 @@ impl Display for AgentSelector {
|
|||
match self {
|
||||
Self::Random => "random",
|
||||
Self::Diffuse => "diffuse",
|
||||
Self::Brutus => "brutus",
|
||||
Self::Chase => "chase",
|
||||
Self::Human => "human",
|
||||
}
|
||||
|
|
100
src/main.rs
100
src/main.rs
|
@ -1,7 +1,11 @@
|
|||
use std::cmp::Ordering;
|
||||
use std::{
|
||||
cmp::Ordering,
|
||||
io::{stdout, Write},
|
||||
};
|
||||
|
||||
use anyhow::{bail, Result};
|
||||
use clap::Parser;
|
||||
use rayon::iter::{IntoParallelIterator, ParallelIterator};
|
||||
use termion::color::{self};
|
||||
|
||||
mod agents;
|
||||
|
@ -77,6 +81,9 @@ fn play(
|
|||
);
|
||||
is_first_turn = false;
|
||||
|
||||
print!("Thinking...");
|
||||
stdout().flush()?;
|
||||
|
||||
// Take action
|
||||
let action = if is_maxi_turn {
|
||||
maxi.step_max(&board)?
|
||||
|
@ -114,68 +121,65 @@ fn play(
|
|||
fn main() -> Result<()> {
|
||||
let cli = cli::Cli::parse();
|
||||
|
||||
rayon::ThreadPoolBuilder::new()
|
||||
.num_threads(8)
|
||||
.build_global()
|
||||
.unwrap();
|
||||
|
||||
if cli.repeat > 1 {
|
||||
let mut red_wins = 0f32;
|
||||
let mut blue_wins = 0f32;
|
||||
let x = (0..cli.repeat)
|
||||
.into_par_iter()
|
||||
.filter_map(|_| {
|
||||
let mut maxi = cli.red.get_maximizer(Player::Red);
|
||||
let mut mini = cli.blue.get_minimizer(Player::Blue);
|
||||
let red_board = match play_silent(&mut *maxi, &mut *mini) {
|
||||
Ok(x) => x,
|
||||
Err(e) => {
|
||||
println!("Error: {e}");
|
||||
return None;
|
||||
}
|
||||
};
|
||||
|
||||
for _ in 0..cli.repeat {
|
||||
let mut maxi = cli.red.get_maximizer(Player::Red);
|
||||
let mut mini = cli.blue.get_minimizer(Player::Blue);
|
||||
let red_board = match if cli.silent {
|
||||
play_silent(&mut *maxi, &mut *mini)
|
||||
} else {
|
||||
play(&mut *maxi, &mut *mini)
|
||||
} {
|
||||
Ok(x) => x,
|
||||
Err(e) => {
|
||||
println!("Error: {e}");
|
||||
continue;
|
||||
}
|
||||
};
|
||||
let mut maxi = cli.blue.get_maximizer(Player::Blue);
|
||||
let mut mini = cli.red.get_minimizer(Player::Red);
|
||||
let blue_board = match play_silent(&mut *maxi, &mut *mini) {
|
||||
Ok(x) => x,
|
||||
Err(e) => {
|
||||
println!("Error: {e}");
|
||||
return None;
|
||||
}
|
||||
};
|
||||
|
||||
let mut maxi = cli.blue.get_maximizer(Player::Blue);
|
||||
let mut mini = cli.red.get_minimizer(Player::Red);
|
||||
let blue_board = match if cli.silent {
|
||||
play_silent(&mut *maxi, &mut *mini)
|
||||
} else {
|
||||
play(&mut *maxi, &mut *mini)
|
||||
} {
|
||||
Ok(x) => x,
|
||||
Err(e) => {
|
||||
println!("Error: {e}");
|
||||
continue;
|
||||
match red_board.evaluate().partial_cmp(&blue_board.evaluate()) {
|
||||
Some(Ordering::Equal) => None,
|
||||
Some(Ordering::Greater) => Some(Player::Red),
|
||||
Some(Ordering::Less) => Some(Player::Blue),
|
||||
None => {
|
||||
println!("Error");
|
||||
None
|
||||
}
|
||||
}
|
||||
};
|
||||
})
|
||||
.collect::<Vec<_>>();
|
||||
|
||||
match red_board.evaluate().partial_cmp(&blue_board.evaluate()) {
|
||||
Some(Ordering::Equal) => {}
|
||||
Some(Ordering::Greater) => red_wins += 1.0,
|
||||
Some(Ordering::Less) => blue_wins += 1.0,
|
||||
None => {
|
||||
println!("Error");
|
||||
}
|
||||
}
|
||||
}
|
||||
let red_wins = x.iter().filter(|x| **x == Player::Red).count();
|
||||
let blue_wins = x.iter().filter(|x| **x == Player::Blue).count();
|
||||
|
||||
println!("Played {} rounds\n", cli.repeat);
|
||||
println!(
|
||||
"Red win rate: {:.2} ({})",
|
||||
red_wins / cli.repeat as f32,
|
||||
red_wins as f32 / cli.repeat as f32,
|
||||
cli.red,
|
||||
);
|
||||
println!(
|
||||
"Blue win rate: {:.2} ({}) ",
|
||||
blue_wins / cli.repeat as f32,
|
||||
blue_wins as f32 / cli.repeat as f32,
|
||||
cli.blue,
|
||||
);
|
||||
} else {
|
||||
let mut maxi = cli.red.get_maximizer(Player::Red);
|
||||
let mut mini = cli.blue.get_minimizer(Player::Blue);
|
||||
let red_board = if cli.silent {
|
||||
play_silent(&mut *maxi, &mut *mini)
|
||||
} else {
|
||||
play(&mut *maxi, &mut *mini)
|
||||
}?;
|
||||
let red_board = play(&mut *maxi, &mut *mini)?;
|
||||
|
||||
if red_board.is_done() {
|
||||
println!(
|
||||
|
@ -196,11 +200,7 @@ fn main() -> Result<()> {
|
|||
|
||||
let mut maxi = cli.blue.get_maximizer(Player::Blue);
|
||||
let mut mini = cli.red.get_minimizer(Player::Red);
|
||||
let blue_board = if cli.silent {
|
||||
play_silent(&mut *maxi, &mut *mini)
|
||||
} else {
|
||||
play(&mut *maxi, &mut *mini)
|
||||
}?;
|
||||
let blue_board = play(&mut *maxi, &mut *mini)?;
|
||||
|
||||
if blue_board.is_done() {
|
||||
println!(
|
||||
|
|
Loading…
Reference in New Issue