Angel problem

Last updated
The blue dotted region shows where an angel of power 3 could reach Angel problem.svg
The blue dotted region shows where an angel of power 3 could reach

The angel problem is a question in combinatorial game theory proposed by John Horton Conway. The game is commonly referred to as the angels and devils game. [1] The game is played by two players called the angel and the devil. It is played on an infinite chessboard (or equivalently the points of a 2D lattice). The angel has a power k (a natural number 1 or higher), specified before the game starts. The board starts empty with the angel in one square. On each turn, the angel jumps to a different empty square which could be reached by at most k moves of a chess king, i.e. the distance from the starting square is at most k in the infinity norm. The devil, on its turn, may add a block on any single square not containing the angel. The angel may leap over blocked squares, but cannot land on them. The devil wins if the angel is unable to move. The angel wins by surviving indefinitely.

Contents

The angel problem is: can an angel with high enough power win?

There must exist a winning strategy for one of the players. If the devil can force a win then it can do so in a finite number of moves. If the devil cannot force a win then there is always an action that the angel can take to avoid losing and a winning strategy for it is always to pick such a move. More abstractly, the "pay-off set" (i.e., the set of all plays in which the angel wins) is a closed set (in the natural topology on the set of all plays), and it is known that such games are determined. Of course, for any infinite game, if player 2 doesn't have a winning strategy, player 1 can always pick a move that leads to a position where player 2 doesn't have a winning strategy, but in some games, simply playing forever doesn't confer a win to player 1, so undetermined games may exist.

Conway offered a reward for a general solution to this problem ($100 for a winning strategy for an angel of sufficiently high power, and $1000 for a proof that the devil can win irrespective of the angel's power). Progress was made first in higher dimensions. In late 2006, the original problem was solved when independent proofs appeared, showing that an angel can win. Bowditch proved that a 4-angel (that is, an angel with power k=4) can win [2] and Máthé [3] and Kloster [4] gave proofs that a 2-angel can win.

Basic strategies and why they don't work

Many intuitive escape strategies for the angel can be defeated. For example, if the angel tries to run away from near blocks, the devil can make a giant horseshoe far to the north, then prod the angel into the trap by repeatedly eating the square just to the south of the angel. If the angel tries to avoid traps set very far away, the devil can make a small horseshoe to the north, then prod the angel into the trap by eating the squares far to the south.

It seems that the angel should be able to win by moving north as fast as he can, combined with occasional zigzags to the east or west to avoid any obvious traps. This strategy can be defeated by noting that this angel's possible future positions lie in a cone, and the devil can build a wall across the cone in the distance in a certain manner, so that when the angel finally arrives at the distance, the devil has created an impenetrable wall, and since the angel insists on moving north, the angel cannot move at all.

History

The problem was first published in the 1982 book Winning Ways by Berlekamp, Conway, and Guy, [5] under the name "the angel and the square-eater." In two dimensions, some early partial results included:

In three dimensions, it was shown that:

Finally, in 2006 (not long after the publication of Peter Winkler's book Mathematical Puzzles, which helped publicize the angel problem) there emerged four independent and almost simultaneous proofs that the angel has a winning strategy in two dimensions. Brian Bowditch's proof works for the 4-angel, while Oddvar Kloster's proof and András Máthé's proof work for the 2-angel. Additionally, Peter Gacs has a claimed proof Archived 2016-03-04 at the Wayback Machine which requires a much stronger angel; the details are fairly complex and have not been reviewed by a journal for accuracy. The proofs by Bowditch and Máthé have been published in Combinatorics, Probability and Computing . The proof by Kloster has been published in Theoretical Computer Science .

Further unsolved questions

In 3D, given that the angel always increases its y-coordinate, and that the devil is limited to three planes, it is unknown whether the devil has a winning strategy.

Proof sketches

Kloster's 2-angel proof

Oddvar Kloster discovered a constructive algorithm to solve the problem with a 2-angel. This algorithm is quite simple and also optimal, since, as noted above, the devil has a winning strategy against a 1-angel.

We start out by drawing a vertical line immediately to the left of the angel's starting position, down to and up to . This line represents the path the angel will take, which will be updated after each of the devil's moves, and partitions the board's squares into a "left set" and a "right set." Once a square becomes part of the left set, it will remain so for the remainder of the game, and the angel will not make any future moves to any of these squares. Every time the devil blocks off a new square, we search over all possible modifications to the path such that we move one or more squares in the right set which the devil has blocked off into the left set. We will only do this if the path increases in length by no more than twice the number of blocked squares moved into the left set. Of such qualifying paths, we choose one that moves the greatest number of blocked off squares into the left set. The angel then makes two steps along this path, keeping the path to its left when moving in the forward direction (so if the devil were not blocking off squares, the angel would travel north indefinitely). Note that when going clockwise around a corner, the angel will not move for one step, because the two segments touching the corner have the same square to their right.

Máthé's 2-angel proof

Máthé [3] introduces the nice devil, which never destroys a square that the angel could have chosen to occupy on an earlier turn. When the angel plays against the nice devil it concedes defeat if the devil manages to confine it to a finite bounded region of the board (otherwise the angel could just hop back and forth between two squares and never lose). Máthé's proof breaks into two parts:

  1. he shows that if the angel wins against the nice devil, then the angel wins against the real devil;
  2. he gives an explicit winning strategy for the angel against the nice devil.

Roughly speaking, in the second part, the angel wins against the nice devil by pretending that the entire left half-plane is destroyed (in addition to any squares actually destroyed by the nice devil), and treating destroyed squares as the walls of a maze, which it then skirts by means of a "hand-on-the-wall" technique. That is, the angel keeps its left hand on the wall of the maze and runs alongside the wall. One then proves that a nice devil cannot trap an angel that adopts this strategy.

The proof of the first part is by contradiction, and hence Máthé's proof does not immediately yield an explicit winning strategy against the real devil. However, Máthé remarks that his proof could in principle be adapted to give such an explicit strategy.

Bowditch's 4-angel proof

Brian Bowditch defines [2] a variant (game 2) of the original game with the following rule changes:

  1. The angel can return to any square it has already been to, even if the devil subsequently tried to block it.
  2. A k-devil must visit a square k times before it is blocked.
  3. The angel moves either up, down, left or right by one square (a duke move).
  4. To win, the angel must trace out a circuitous path (defined below).

A circuitous path is a path where is a semi-infinite arc (a non self-intersecting path with a starting point but no ending point) and are pairwise disjoint loops with the following property:

(To be well defined must begin and end at the end point of and must end at the starting point of .)

Bowditch considers a variant (game 1) of the game with the changes 2 and 3 with a 5-devil. He then shows that a winning strategy in this game will yield a winning strategy in our original game for a 4-angel. He then goes on to show that an angel playing a 5-devil (game 2) can achieve a win using a fairly simple algorithm.

Bowditch claims that a 4-angel can win the original version of the game by imagining a phantom angel playing a 5-devil in the game 2.

The angel follows the path the phantom would take but avoiding the loops. Hence as the path is a semi-infinite arc the angel does not return to any square it has previously been to and so the path is a winning path even in the original game.

3D version of the problem

"Guardian" proof

The proof, which shows that in a three-dimensional version of the game a high powered angel has a winning strategy, makes use of "guardians". For each cube of any size, there is a guardian that watches over that cube. The guardians decide at each move whether the cube they are watching over is unsafe, safe, or almost safe. The definitions of "safe" and "almost safe" need to be chosen to ensure this works. This decision is based purely on the density of blocked points in that cube and the size of that cube.

If the angel is given no orders, then it just moves up. If some cubes that the angel is occupying cease to be safe, then the guardian of the biggest of these cubes is instructed to arrange for the angel to leave through one of the borders of that cube. If a guardian is instructed to escort the angel out of its cube to a particular face, the guardian does so by plotting a path of subcubes that are all safe. The guardians in these cubes are then instructed to escort the angel through their respective subcubes. The angel's path in a given subcube is not determined until the angel arrives at that cube. Even then, the path is only determined roughly. This ensures the devil cannot just choose a place on the path sufficiently far along it and block it.

The strategy can be proven to work because the time it takes the devil to convert a safe cube in the angel's path to an unsafe cube is longer than the time it takes the angel to get to that cube.

This proof was published by Imre Leader and Béla Bollobás in 2006. [8] A substantially similar proof was published by Martin Kutz in 2005. [6] [9]

See also

Related Research Articles

<span class="mw-page-title-main">Spinor</span> Non-tensorial representation of the spin group

In geometry and physics, spinors are elements of a complex number-based vector space that can be associated with Euclidean space. A spinor transforms linearly when the Euclidean space is subjected to a slight (infinitesimal) rotation, but unlike geometric vectors and tensors, a spinor transforms to its negative when the space rotates through 360°. It takes a rotation of 720° for a spinor to go back to its original state. This property characterizes spinors: spinors can be viewed as the "square roots" of vectors.

<span class="mw-page-title-main">Simplex</span> Multi-dimensional generalization of triangle

In geometry, a simplex is a generalization of the notion of a triangle or tetrahedron to arbitrary dimensions. The simplex is so-named because it represents the simplest possible polytope in any given dimension. For example,

In game theory, the Nash equilibrium is the most commonly-used solution concept for non-cooperative games. A Nash equilibrium is a situation where no player could gain by changing their own strategy. The idea of Nash equilibrium dates back to the time of Cournot, who in 1838 applied it to his model of competition in an oligopoly.

<span class="mw-page-title-main">Busy beaver</span> Longest-running turing machine of a given size

In theoretical computer science, the busy beaver game aims at finding a terminating program of a given size that either produces the most output possible, or runs for the longest number of steps. Since an endlessly looping program producing infinite output or running for infinite time is easily conceived, such programs are excluded from the game. Rather than traditional programming languages, the programs used in the game are n-state Turing machines, one of the first mathematical models of computation.

<span class="mw-page-title-main">Singular value decomposition</span> Matrix decomposition

In linear algebra, the singular value decomposition (SVD) is a factorization of a real or complex matrix into a rotation, followed by a rescaling followed by another rotation. It generalizes the eigendecomposition of a square normal matrix with an orthonormal eigenbasis to any matrix. It is related to the polar decomposition.

<span class="mw-page-title-main">Random walk</span> Process forming a path from many random steps

In mathematics, a random walk, sometimes known as a drunkard's walk, is a random process that describes a path that consists of a succession of random steps on some mathematical space.

The Ising model, named after the physicists Ernst Ising and Wilhelm Lenz, is a mathematical model of ferromagnetism in statistical mechanics. The model consists of discrete variables that represent magnetic dipole moments of atomic "spins" that can be in one of two states. The spins are arranged in a graph, usually a lattice, allowing each spin to interact with its neighbors. Neighboring spins that agree have a lower energy than those that disagree; the system tends to the lowest energy but heat disturbs this tendency, thus creating the possibility of different structural phases. The model allows the identification of phase transitions as a simplified model of reality. The two-dimensional square-lattice Ising model is one of the simplest statistical models to show a phase transition.

In game theory, the best response is the strategy which produces the most favorable outcome for a player, taking other players' strategies as given. The concept of a best response is central to John Nash's best-known contribution, the Nash equilibrium, the point at which each player in a game has selected the best response to the other players' strategies.

In coding theory, block codes are a large and important family of error-correcting codes that encode data in blocks. There is a vast number of examples for block codes, many of which have a wide range of practical applications. The abstract definition of block codes is conceptually useful because it allows coding theorists, mathematicians, and computer scientists to study the limitations of all block codes in a unified way. Such limitations often take the form of bounds that relate different parameters of the block code to each other, such as its rate and its ability to detect and correct errors.

<span class="mw-page-title-main">Linear discriminant analysis</span> Method used in statistics, pattern recognition, and other fields

Linear discriminant analysis (LDA), normal discriminant analysis (NDA), or discriminant function analysis is a generalization of Fisher's linear discriminant, a method used in statistics and other fields, to find a linear combination of features that characterizes or separates two or more classes of objects or events. The resulting combination may be used as a linear classifier, or, more commonly, for dimensionality reduction before later classification.

Game theory is the branch of mathematics in which games are studied: that is, models describing human behaviour. This is a glossary of some terms of the subject.

Determinacy is a subfield of set theory, a branch of mathematics, that examines the conditions under which one or the other player of a game has a winning strategy, and the consequences of the existence of such strategies. Alternatively and similarly, "determinacy" is the property of a game whereby such a strategy exists. Determinacy was introduced by Gale and Stewart in 1950, under the name "determinateness".

<span class="mw-page-title-main">Kelly criterion</span> Formula for bet sizing that maximizes the expected logarithmic value

In probability theory, the Kelly criterion is a formula for sizing a sequence of bets by maximizing the long-term expected value of the logarithm of wealth, which is equivalent to maximizing the long-term expected geometric growth rate. John Larry Kelly Jr., a researcher at Bell Labs, described the criterion in 1956.

Covariance matrix adaptation evolution strategy (CMA-ES) is a particular kind of strategy for numerical optimization. Evolution strategies (ES) are stochastic, derivative-free methods for numerical optimization of non-linear or non-convex continuous optimization problems. They belong to the class of evolutionary algorithms and evolutionary computation. An evolutionary algorithm is broadly based on the principle of biological evolution, namely the repeated interplay of variation and selection: in each generation (iteration) new individuals are generated by variation of the current parental individuals, usually in a stochastic way. Then, some individuals are selected to become the parents in the next generation based on their fitness or objective function value . Like this, individuals with better and better -values are generated over the generation sequence.

In game theory, a stochastic game, introduced by Lloyd Shapley in the early 1950s, is a repeated game with probabilistic transitions played by one or more players. The game is played in a sequence of stages. At the beginning of each stage the game is in some state. The players select actions and each player receives a payoff that depends on the current state and the chosen actions. The game then moves to a new random state whose distribution depends on the previous state and the actions chosen by the players. The procedure is repeated at the new state and play continues for a finite or infinite number of stages. The total payoff to a player is often taken to be the discounted sum of the stage payoffs or the limit inferior of the averages of the stage payoffs.

Brian Hayward Bowditch is a British mathematician known for his contributions to geometry and topology, particularly in the areas of geometric group theory and low-dimensional topology. He is also known for solving the angel problem. Bowditch holds a chaired Professor appointment in Mathematics at the University of Warwick.

In descriptive set theory, the Borel determinacy theorem states that any Gale–Stewart game whose payoff set is a Borel set is determined, meaning that one of the two players will have a winning strategy for the game. A Gale–Stewart game is a possibly infinite two-player game, where both players have perfect information and no randomness is involved.

Quantum refereed game in quantum information processing is a class of games in the general theory of quantum games. It is played between two players, Alice and Bob, and arbitrated by a referee. The referee outputs the pay-off for the players after interacting with them for a fixed number of rounds, while exchanging quantum information.

In mathematics, a Hurewicz space is a topological space that satisfies a certain basic selection principle that generalizes σ-compactness. A Hurewicz space is a space in which for every sequence of open covers of the space there are finite sets such that every point of the space belongs to all but finitely many sets .

In mathematics, especially mathematical logic, graph theory and number theory, the Buchholz hydra game is a type of hydra game, which is a single-player game based on the idea of chopping pieces off a mathematical tree. The hydra game can be used to generate a rapidly growing function, , which eventually dominates all recursive functions that are provably total in "", and the termination of all hydra games is not provably total in .

References

  1. John H. Conway, The angel problem , in: Richard Nowakowski (editor) Games of No Chance, volume 29 of MSRI Publications, pages 312, 1996.
  2. 1 2 Brian H. Bowditch, "The angel game in the plane", Combin. Probab. Comput. 16(3):345-362, 2007.
  3. 1 2 András Máthé, "The angel of power 2 wins", Combin. Probab. Comput. 16(3):363-374, 2007
  4. O. Kloster, A solution to the angel problem. Theoretical Computer Science, vol. 389 (2007), no. 1-2, pp. 152161
  5. Berlekamp, Elwyn R.; Conway, John H.; Guy, Richard K. (1982), "Chapter 19: The King and the Consumer", Winning Ways for your Mathematical Plays, Volume 2: Games in Particular, Academic Press, pp. 607–634.
  6. 1 2 Martin Kutz, The Angel Problem, Positional Games, and Digraph Roots, PhD Thesis FU Berlin, 2004
  7. B. Bollobás and I. Leader, The angel and the devil in three dimensions. Journal of Combinatorial Theory, Series A. vol. 113 (2006), no. 1, pp. 176184
  8. B. Bollobás and I. Leader, The angel and the devil in three dimensions. Journal of Combinatorial Theory, Series A. vol. 113 (2006), no. 1, pp. 176184
  9. Martin Kutz, Conway's Angel in three dimensions, Theoret. Comp. Sci. 349(3):443–451, 2005.