Connect Four

credit for this assignment: Finn Voichick and Dennis Cosgrove

Motivation

Minimax is an important concept in game theory and search.

Negamax is a variant which relies on $\max(a,b)=-\min(-a,-b)$

While this technique is applicable to Chess (as Deep Blue employed to defeat Kasparov), we choose Connect Four as our context since it has a simpler game mechanic.

While the core part of searches like Minimax may be easy to parallelize, critical aspects such as alpha-beta pruning are more challenging.

Background

Tutorial

Solving Connect Four

Wikipedia

Minimax

Negamax

The Core Questions

• What are the tasks?
• What is the data?
• Is the data mutable?
• If so, how is it shared?

Code To Use

connectfour.core

interface Board

isDone()

getWinner()

getCurrentPlayer()

getTurnsPlayed()

createNextBoard(int column)

java.util

class Optional<T>

java.util.function

interface ToDoubleFunction<T>

applyAsDouble(value)

interface IntPredicate

test(value)

Mistakes To Avoid

Warning:Do NOT be lured in be Double.MIN_VALUE. Use Double.NEGATIVE_INFINITY instead.

Warning: If you are going to use Double.NaN to indicate an invalid/unsearched column (which as an implementation detail, is not the worst choice) be sure you know what you are doing. Double.NaN's semantics can absolutely be leveraged, but it can be tricky.

Code To Implement

NOTE: While you should defer to the IntPredicate searchAtDepth for when to continue to search (test returns true) or when to return an evaluation (test returns false), it is up to you to decide when to search in parallel and when to fall back to sequential search.

Negamax

class:	ConnectFour.java
methods:	negamaxKernel selectNextColumn
package:	connectfour.studio
source folder:	student/src/main/java

method: private static double negamaxKernel(Board board, ToDoubleFunction<Board> heuristic, IntPredicate searchAtDepth, int currentDepth) (parallel implementation required)

method: public static Optional<Integer> selectNextColumn(Board board, ToDoubleFunction<Board> heuristic, IntPredicate searchAtDepth) (parallel implementation required)

Win or Lose Heuristic

class:	WinOrLoseHeuristic.java
methods:	applyAsDouble
package:	connectfour.studio
source folder:	student/src/main/java

method: public double applyAsDouble(Board board) (sequential implementation only)

Evaluate the current state of the Board. You should return a negative number if you have lost. You should return less negative numbers for losses that occur later. Put another way, draws should return 0. Losses on the final turn should return -1. Losses on the third to last turn should return -3. Wins should return the analogous positive numbers.

Interestingly (at least to the Professor), if you build your algorithm in an expected way, you will only need to handle draws as well as (wins or losses). Which one is it? Wins? Or losses?

OpenEndedHeuristic (Optional)

class:	OpenEndedHeuristic.java
methods:	applyAsDouble
package:	connectfour.challenge
source folder:	student/src/main/java

method: public double applyAsDouble(Board board) (sequential implementation only)

Testing Your Solution

Correctness

class:	ConnectFourTestSuite.java
package:	connnectfour.studio
source folder:	testing/src/test/java

Some preliminary tests use a simple end game board, destined for a draw, where the last three searches will end in Optional.of(6).

Visualization

class:	ConnectFourViz.java	VIZ
package:	connnectfour.viz.game
source folder:	student/src//java