Cargo.lock

@@ -120,31 +120,6 @@ 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"
@@ -202,7 +177,6 @@ dependencies = [
  "clap",
  "itertools",
  "rand",
- "rayon",
  "termion",
 ]
 
@@ -266,26 +240,6 @@ dependencies = [
  "getrandom",
 ]
 
-[[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"
 version = "0.4.1"

Cargo.toml

@@ -8,5 +8,4 @@ anyhow = "1.0.80"
 clap = { version = "4.5.1", features = ["derive"] }
 itertools = "0.12.1"
 rand = "0.8.5"
-rayon = "1.9.0"
 termion = "3.0.0"

README.md

@@ -22,15 +22,7 @@ As always, run this project with `cargo run`. The app takes one argument by defa
  - `random`: Play against a random agent (very easy)
  - `chase`: Play against a simple extremum-chasing agent (easy)
  - `diffuse`: Play against a slightly more intellegent extremum chaser (medium)
- - `brutus`: Play against a simple brute-force agent (hard)
 
-For example, `cargo run -- random` will start a game against a random player. Use your arrow keys and space bar to play.
+For example, `cargo run -- random` will play a game against a random player. Use your arrow keys and space bar to play the game.
 
-Additional options are available, see `cargo run -- --help`.
+Additional options are available, see `cargo run -- --help`.
-
-Win rates against random are as follows:
- - `human`: ~100%
- - `random`: ~50%
- - `chase`: ~70%
- - `diffuse`: ~76%
- - `brutus`: ~90%

src/agents/brutus.rs

@@ -1,142 +0,0 @@
-use std::{cmp::Ordering, iter};
-
-use anyhow::Result;
-use itertools::Itertools;
-use rand::{seq::SliceRandom, thread_rng};
-use rayon::iter::{ParallelBridge, ParallelIterator};
-
-use super::{Agent, Chase, MaximizerAgent, MinimizerAgent};
-use crate::{
-	agents::{util::best_board_noop, Diffuse},
-	board::{Board, PlayerAction},
-	util::{Player, Symb},
-};
-
-pub struct Brutus {
-	player: Player,
-}
-
-impl Brutus {
-	pub fn new(player: Player) -> Self {
-		Self { player }
-	}
-
-	fn step(&mut self, board: &Board, minimize: bool) -> Result<PlayerAction> {
-		let symbols = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div]
-			.into_iter()
-			.filter(|x| !board.contains(*x))
-			.collect_vec();
-
-		if symbols.is_empty() {
-			return if minimize {
-				Chase::new(self.player).step_min(board)
-			} else {
-				Chase::new(self.player).step_max(board)
-			};
-		}
-
-		// Number of free slots
-		let n_free = board.get_board().iter().filter(|x| x.is_none()).count();
-
-		// Number of slots we need to fill with numbers
-		// Add one if we have two or fewer symbols available, so that we can
-		// account for one unused symbol while keeping a reasonable runtime
-		let n_fill = n_free - symbols.len() + if symbols.len() <= 2 { 1 } else { 0 };
-
-		let mut items = iter::repeat(None)
-			.take(n_fill)
-			.chain(symbols.iter().map(|x| Some(x.clone())))
-			.permutations(n_free)
-			.unique()
-			.par_bridge()
-			.filter_map(move |x| {
-				let mut tmp_board = board.clone();
-
-				for (i, s) in x.iter().enumerate() {
-					if let Some(s) = s {
-						let pos = board.ith_empty_slot(i).unwrap();
-						if !tmp_board.can_play(&PlayerAction { symb: *s, pos }) {
-							return None;
-						}
-						tmp_board.get_board_mut()[pos] = Some(*s);
-					}
-				}
-
-				let min = best_board_noop(&tmp_board, true);
-				let max = best_board_noop(&tmp_board, false);
-				if min.is_none() || max.is_none() {
-					return None;
-				}
-
-				let v_min = min.unwrap().evaluate().unwrap();
-				let v_max = max.unwrap().evaluate().unwrap();
-				let v = v_min + v_max / 2.0;
-
-				Some((tmp_board, v))
-			})
-			.collect::<Vec<_>>();
-
-		if minimize {
-			// Sort from smallest to biggest midpoint
-			items.sort_by(|a, b| a.1.partial_cmp(&b.1).unwrap_or(Ordering::Equal));
-		} else {
-			items.sort_by(|a, b| b.1.partial_cmp(&a.1).unwrap_or(Ordering::Equal));
-		}
-
-		// TODO: why can `items` be empty?
-		// We shouldn't need this escape hatch
-		if items.is_empty() {
-			return if minimize {
-				Diffuse::new(self.player).step_min(board)
-			} else {
-				Diffuse::new(self.player).step_max(board)
-			};
-		}
-
-		let (t, _) = items.first().unwrap();
-
-		let mut symbols = symbols.clone();
-		symbols.shuffle(&mut thread_rng());
-
-		// Place a random unused symbol
-		for target_s in symbols {
-			for (i, s) in t.get_board().iter().enumerate() {
-				if let Some(s) = s {
-					if board.get_board()[i].is_none() && target_s == *s {
-						return Ok(PlayerAction { pos: i, symb: *s });
-					}
-				}
-			}
-		}
-
-		// Final escape hatch, if we didn't decide to place any symbols
-		// (which is possible, since we add one to free_spots above!)
-		if minimize {
-			Chase::new(self.player).step_min(board)
-		} else {
-			Chase::new(self.player).step_max(board)
-		}
-	}
-}
-
-impl Agent for Brutus {
-	fn name(&self) -> &'static str {
-		"Brutus"
-	}
-
-	fn player(&self) -> Player {
-		self.player
-	}
-}
-
-impl MinimizerAgent for Brutus {
-	fn step_min(&mut self, board: &Board) -> Result<PlayerAction> {
-		self.step(board, true)
-	}
-}
-
-impl MaximizerAgent for Brutus {
-	fn step_max(&mut self, board: &Board) -> Result<PlayerAction> {
-		self.step(board, false)
-	}
-}

src/agents/diffuse.rs

@@ -1,5 +1,4 @@
 use anyhow::Result;
-use rand::{seq::SliceRandom, thread_rng};
 
 use super::{Agent, Chase, MaximizerAgent, MinimizerAgent, Random};
 use crate::{
@@ -10,7 +9,6 @@ use crate::{
 /// A simple "operator diffusion" MINIMIZER agent.
 ///
 /// Tries to keep operators as far apart as possible, denying large numbers.
-/// Places numbers using the same algorithm as chase.
 pub struct Diffuse {
 	player: Player,
 }
@@ -88,9 +86,9 @@ impl Agent for Diffuse {
 
 impl MinimizerAgent for Diffuse {
 	fn step_min(&mut self, board: &Board) -> Result<PlayerAction> {
-		let mut x = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div];
+		let symb = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div]
-		x.shuffle(&mut thread_rng());
+			.iter()
-		let symb = x.iter().find(|x| !board.contains(**x));
+			.find(|x| !board.contains(**x));
 
 		if let Some(symb) = symb {
 			Ok(self.step_symb(board, *symb))
@@ -103,9 +101,9 @@ impl MinimizerAgent for Diffuse {
 
 impl MaximizerAgent for Diffuse {
 	fn step_max(&mut self, board: &Board) -> Result<PlayerAction> {
-		let mut x = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div];
+		let symb = [Symb::Minus, Symb::Times, Symb::Plus, Symb::Div]
-		x.shuffle(&mut thread_rng());
+			.iter()
-		let symb = x.iter().find(|x| !board.contains(**x));
+			.find(|x| !board.contains(**x));
 
 		if let Some(symb) = symb {
 			Ok(self.step_symb(board, *symb))

src/agents/human.rs

@@ -195,7 +195,7 @@ impl Human {
 
 impl Agent for Human {
 	fn name(&self) -> &'static str {
-		"Human"
+		"Player"
 	}
 
 	fn player(&self) -> Player {

src/agents/mod.rs

@@ -1,11 +1,9 @@
-mod brutus;
 mod chase;
 mod diffuse;
 mod human;
 mod random;
 pub mod util;
 
-pub use brutus::Brutus;
 pub use chase::Chase;
 pub use diffuse::Diffuse;
 pub use human::Human;

src/agents/util/partials.rs

@@ -1,10 +1,10 @@
 use itertools::Itertools;
-use std::{mem::swap, num::NonZeroU8};
+use std::num::NonZeroU8;
 
 use crate::{board::Board, util::Symb};
 
-/// Returns an iterator of (idx, coords, char_idx, f32) for each empty slot in the listed partials.
+/// Returns an iterator of (sort, coords, char_idx, f32) for each empty slot in the listed partials.
-/// - idx is the index of this slot in the board string.
+/// - sort is the index of this slot.
 /// - coords are the coordinate of this slot's partial
 /// - char_idx is the index of this slot in its partial
 /// - f32 is the influence of this slot
@@ -51,12 +51,16 @@ pub fn free_slots_by_influence(board: &Board) -> Option<Vec<(usize, f32)>> {
 	Some(slots)
 }
 
-/// Find the minimum or maximum possible value of the given board,
+/// Find the maximum possible value of the given board
-/// without adding any operations. Returns None if we couldn't find
+#[allow(dead_code)]
-/// a best board.
+pub fn maximize_value(board: &Board) -> Option<Board> {
-pub fn best_board_noop(board: &Board, minimize: bool) -> Option<Board> {
 	let n_free = board.get_board().iter().filter(|x| x.is_none()).count();
 
+	// Assume we have 10 or fewer available slots
+	if n_free >= 10 {
+		panic!()
+	}
+
 	let available_numbers = (0..=9)
 		.map(|x| match x {
 			0 => Symb::Zero,
@@ -65,36 +69,19 @@ pub fn best_board_noop(board: &Board, minimize: bool) -> Option<Board> {
 		.filter(|x| !board.contains(*x))
 		.collect::<Vec<_>>();
 
-	if n_free > available_numbers.len() {
-		return None;
-	}
-
 	let slots = free_slots_by_influence(board)?;
 
 	let all_symbols = {
-		let mut a = {
+		// We need this many from the bottom, and this many from the top.
-			// Number of slots we want to minimize
+		let neg_count = slots.iter().filter(|(_, x)| *x <= 0.0).count();
-			let mut neg_count = slots.iter().filter(|(_, x)| *x <= 0.0).count();
+		let pos_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();
 
-			if minimize {
+		let mut a_iter = available_numbers
-				swap(&mut neg_count, &mut pos_count);
+			.iter()
-			}
+			.take(neg_count)
+			.chain(available_numbers.iter().rev().take(pos_count).rev());
 
-			available_numbers
+		let mut g = slots
-				.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()
@@ -114,32 +101,37 @@ pub fn best_board_noop(board: &Board, minimize: bool) -> Option<Board> {
 			// of this set of sets
 			.multi_cartesian_product()
 			.map(|x| x.iter().flatten().cloned().collect_vec())
-			// Finally, attach the coordinate of each slot to each symbol
+			.map(|v| slots.iter().zip(v).collect_vec())
-			.map(|v| slots.iter().map(|x| x.0).zip(v).collect_vec())
+			.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())
 	};
 
 	let mut best_board = None;
 	let mut best_value = None;
-	for i_iter in all_symbols {
+	for i in all_symbols {
-		let mut tmp_board = board.clone();
+		let mut i_iter = i.iter();
-		for (i, s) in i_iter {
+		let filled = Board::from_board(board.get_board().map(|x| match x {
-			tmp_board.get_board_mut()[i] = Some(s);
+			None => i_iter.next().cloned(),
-		}
+			_ => x,
+		}));
 
-		let val = tmp_board.evaluate();
+		let val = filled.evaluate();
 
 		if let Some(val) = val {
-			if minimize {
+			if let Some(best) = best_value {
-				if best_value.is_none() || val < best_value.unwrap() {
+				if val > best {
 					best_value = Some(val);
-					best_board = Some(tmp_board)
+					best_board = Some(filled)
 				}
 			} else {
-				if best_value.is_none() || val > best_value.unwrap() {
+				best_value = Some(val);
-					best_value = Some(val);
+				best_board = Some(filled)
-					best_board = Some(tmp_board)
-				}
 			}
 		}
 	}

src/board/board.rs

@@ -1,6 +1,6 @@
 use anyhow::Result;
 use itertools::Itertools;
-use std::fmt::{Debug, Display, Write};
+use std::fmt::{Display, Write};
 use termion::color::{self, Color};
 
 use super::{PlayerAction, TreeElement};
@@ -74,12 +74,6 @@ 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 {
@@ -99,24 +93,6 @@ 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
 	}

src/cli.rs

@@ -3,7 +3,7 @@ use std::fmt::Display;
 use clap::{Parser, ValueEnum};
 
 use crate::{
-	agents::{Brutus, Chase, Diffuse, Human, MaximizerAgent, MinimizerAgent, Random},
+	agents::{Chase, Diffuse, Human, MaximizerAgent, MinimizerAgent, Random},
 	util::Player,
 };
 
@@ -18,8 +18,14 @@ 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)]
@@ -35,9 +41,6 @@ pub enum AgentSelector {
 
 	/// A smarter extremum-chaser (medium)
 	Diffuse,
-
-	/// A very smart brute-force agent (hard)
-	Brutus,
 }
 
 impl AgentSelector {
@@ -46,7 +49,6 @@ 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)),
 		}
 	}
@@ -56,7 +58,6 @@ 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)),
 		}
 	}
@@ -70,7 +71,6 @@ impl Display for AgentSelector {
 			match self {
 				Self::Random => "random",
 				Self::Diffuse => "diffuse",
-				Self::Brutus => "brutus",
 				Self::Chase => "chase",
 				Self::Human => "human",
 			}

src/main.rs

@@ -1,11 +1,7 @@
-use std::{
+use std::cmp::Ordering;
-	cmp::Ordering,
-	io::{stdout, Write},
-};
 
 use anyhow::{bail, Result};
 use clap::Parser;
-use rayon::iter::{IntoParallelIterator, ParallelIterator};
 use termion::color::{self};
 
 mod agents;
@@ -81,9 +77,6 @@ fn play(
 		);
 		is_first_turn = false;
 
-		print!("Thinking...");
-		stdout().flush()?;
-
 		// Take action
 		let action = if is_maxi_turn {
 			maxi.step_max(&board)?
@@ -121,65 +114,68 @@ fn play(
 fn main() -> Result<()> {
 	let cli = cli::Cli::parse();
 
-	rayon::ThreadPoolBuilder::new()
-		.num_threads(8)
-		.build_global()
-		.unwrap();
-
 	if cli.repeat > 1 {
-		let x = (0..cli.repeat)
+		let mut red_wins = 0f32;
-			.into_par_iter()
+		let mut blue_wins = 0f32;
-			.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;
-					}
-				};
 
-				let mut maxi = cli.blue.get_maximizer(Player::Blue);
+		for _ in 0..cli.repeat {
-				let mut mini = cli.red.get_minimizer(Player::Red);
+			let mut maxi = cli.red.get_maximizer(Player::Red);
-				let blue_board = match play_silent(&mut *maxi, &mut *mini) {
+			let mut mini = cli.blue.get_minimizer(Player::Blue);
-					Ok(x) => x,
+			let red_board = match if cli.silent {
-					Err(e) => {
+				play_silent(&mut *maxi, &mut *mini)
-						println!("Error: {e}");
+			} else {
-						return None;
+				play(&mut *maxi, &mut *mini)
-					}
+			} {
-				};
+				Ok(x) => x,
-
+				Err(e) => {
-				match red_board.evaluate().partial_cmp(&blue_board.evaluate()) {
+					println!("Error: {e}");
-					Some(Ordering::Equal) => None,
+					continue;
-					Some(Ordering::Greater) => Some(Player::Red),
-					Some(Ordering::Less) => Some(Player::Blue),
-					None => {
-						println!("Error");
-						None
-					}
 				}
-			})
+			};
-			.collect::<Vec<_>>();
 
-		let red_wins = x.iter().filter(|x| **x == Player::Red).count();
+			let mut maxi = cli.blue.get_maximizer(Player::Blue);
-		let blue_wins = x.iter().filter(|x| **x == Player::Blue).count();
+			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) => {}
+				Some(Ordering::Greater) => red_wins += 1.0,
+				Some(Ordering::Less) => blue_wins += 1.0,
+				None => {
+					println!("Error");
+				}
+			}
+		}
 
 		println!("Played {} rounds\n", cli.repeat);
 		println!(
 			"Red  win rate: {:.2}  ({})",
-			red_wins as f32 / cli.repeat as f32,
+			red_wins / cli.repeat as f32,
 			cli.red,
 		);
 		println!(
 			"Blue win rate: {:.2}  ({}) ",
-			blue_wins as f32 / cli.repeat as f32,
+			blue_wins / 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 = play(&mut *maxi, &mut *mini)?;
+		let red_board = if cli.silent {
+			play_silent(&mut *maxi, &mut *mini)
+		} else {
+			play(&mut *maxi, &mut *mini)
+		}?;
 
 		if red_board.is_done() {
 			println!(
@@ -200,7 +196,11 @@ fn main() -> Result<()> {
 
 		let mut maxi = cli.blue.get_maximizer(Player::Blue);
 		let mut mini = cli.red.get_minimizer(Player::Red);
-		let blue_board = play(&mut *maxi, &mut *mini)?;
+		let blue_board = if cli.silent {
+			play_silent(&mut *maxi, &mut *mini)
+		} else {
+			play(&mut *maxi, &mut *mini)
+		}?;
 
 		if blue_board.is_done() {
 			println!(