1. Introduction
Game theory studies conflict and cooperation between rational players. To this end, a sophisticated mathematical machinery has been developed that facilitates this reasoning. There are numerous textbooks that can serve as an excellent introduction to this field. In this paper, we shall use just a few fundamental concepts and we refer to [
1,
2] as accessible and user-friendly references, whereas [
3] is a more rigorous exposition. The landmark work “Theory of Games and Economic Behavior” [
4] by John Von Neumann and Oskar Morgenstern is usually credited as being the one responsible for the creation this field. Since then, Game theory has been broadly investigated due to its numerous applications, both in theory and practice. It would not be an exaggeration to claim that today the use of Game theory is pervasive in economics, political and social sciences. It has even been used in such diverse fields as biology and psychology. In every case where at least two entities are either in conflict or cooperate, Game theory provides the proper tools to analyze the situation. The entities are called players, each player has his own goals and the actions of every player affect the other players. Every player has at his disposal a set of actions, from which his set of strategies is determined. The outcome of the game from the point of view of each player is quantitatively assessed by a function that is called utility or payoff function. The players are assumed to be rational, i.e., every player acts so as to maximize his payoff.
Quantum computation is a relatively new field that was initially envisioned by Richard Feynman in the early 1980s. Today, there is a wide interest in this area and, more importantly, actual efforts for the building practical commercial quantum computing machines or at least quantum components. One could argue that quantum computing perceives the actual computation process as a natural phenomenon, in contrast to the known binary logic of classical systems. Technically, a quantum computer is expected to use qubits as the basic unit of computation instead of the classical bit. The transitions among quantum states will be achieved through the application of unitary matrices. It is hoped that the use of quantum or quantum-inspired computing machines will lead to an increase in computational capabilities and efficiency, since the quantum world is inherently probabilistic and non-classical phenomena, such as superposition and entanglement, occur. Up to now, the superiority of quantum methods over classical ones has only been proven for particular classes of problems; nevertheless the performance gains in such cases are tremendous. In the
penny flip game described by Meyer in [
5], the quantum player Q has an overwhelming advantage over the classical player Picard. The recent field of quantum game theory is devoted to the study of quantum techniques in classical games, such as the coin flipping, the prisoners’ dilemma and many others.
Contribution. The main contribution of this work lies in establishing a rigorous connection between finite automata and the
game with all its finite variations. Starting from the automaton that corresponds to the original
game, we construct automata for various interesting variations of the game, before finally presenting a semiautomaton in
Section 7.1 that captures the “essence” of the
game. By this we mean that this semiautomaton serves as a template for building automata (by designating appropriate initial and accepting states) that cover
all possible finite games that can be played between Q and Picard. We point out that the resulting automata are almost identical, since they differ only in the initial state and/or their accepting states; however, these minor differences have a profound effect on the accepting language.
Furthermore, we introduce two novel notions, that of a winning automaton and that of a complete automaton for either player. A winning automaton for either Q or Picard accepts only those words that correspond to actions that allow him to win the game with probability and a complete automaton (for Q or Picard) accepts all such words. This is a powerful tool because it allows us to determine whether or not an arbitrary long sequence of actions guarantees that one of the two players will surely win just be checking if the corresponding word is accepted or not by the complete automaton for that player.
We clarify that the automata we construct do more than simply accept dominant strategies. They are specifically designed to accept sequences of actions by both players, i.e., sequences that contain the actions of both players. This gives a global overview of the evolution of the game from the point of view of both players. Moreover, no information is lost and, in case one wishes to focus only on dominant strategies for a specific player, this can be simply achieved by considering a substring from each accepted word; this substring will contain only the actions of the specific player, disregarding all actions by the other player.
The paper is organized as follows:
Section 2 discusses related work;
Section 3 explains the notation and definitions used throughout the rest of the paper;
Section 4 lays the necessary groundwork for the connection of games with automata;
Section 5 describes the automaton that corresponds to the standard
game;
Section 6 analyzes how one may construct automata that correspond to specific variants of the
game;
Section 7 contains the most important results of this work: the semiautomaton in
Section 7.1 that captures all possible finite games between Q and Picard, and the concepts of winning and complete automata for Q or Picard; and
Section 8 summarizes our results and conclusions and points to directions for future work.
2. Related Work
In 1999, Mayer [
5] introduced the quantum version of the penny flip game with two players and a two dimensional coin. In the original, game the two players are named Q and Picard (from a popular tv series). Picard is restricted to classic strategies, whereas Q is able to use quantum strategies. As a result, Q is able to apply unitary transformations in every possible state of the game. Mayer identifies a winning strategy for Q that boils down to the application of the Hadamard transform. Picard, on the other hand, who can either leave the coin as is or flip it, is bound to lose in every case.
Many articles extended the aforementioned game to an
n-state quantum roulette using various techniques. Salimi et al. [
6] used permutation matrices and the Fourier matrix as a representation of the symmetric group
. They viewed quantum roulette as a typical
n-state quantum system and developed a methodology that allowed them to solve this quantum game for arbitrary
n. As an example, they employed their technique for a quantum roulette with
. Wang et al. [
7] also generalized the coin tossing game to an
n-state game. Ren et al. [
8] developed specific methods that enabled them to solve the problem of quantum coin-tossing in a roulette game. Specifically, they used two methods, which they called analogy and isolation methods respectively, to tackle the above problem. All the previously mentioned articles focused on the expansion of states, essentially converting the coin into a roulette.
Quantum protocols from the fields of quantum and post-quantum cryptography are widely studied in the framework of quantum game theory. Several cryptographic protocols have been developed in order to provide reliable communication between two separate players regarding the coin-tossing game [
9,
10,
11,
12]. Nguyen et al. [
9] analyzed how the performance of a quantum coin tossing experiment should be compared to classical protocols, taking into account the inevitable experimental imperfections. They designed an all-optical fiber experiment, in which a single coin is tossed whose randomness is higher than that of any classical protocol. In the same paper, they presented some easily realizable cheating strategies for Alice and Bob. Berlin et al. [
10] introduced a quantum protocol which they proved to be completely impervious to loss. The protocol is fair when both players have the same probability for a successful cheating upon the outcome of the coin flip. They also gave explicit and optimal cheating strategies for both players. Ambainis [
11] devised a protocol in which a dishonest party will not be able to ensure a specific result with probability greater than
. For this particular protocol, the use of parallelism will not lead to a decrease of its bias. In [
12], Ambainis et al. investigated similar protocols in a context of multiple parties, where it was shown that the coin may not be fixed provided that a fraction of the players remain honest.
Many researchers have investigated turn-based versions of classical games such as the prisoners’ dilemma. One of the first works that associated finite automata with game theory was by Neyman [
13], where he studied how finite automata can be used to acquire the complexity of strategies available to players. Rubinstein [
14] studied a variation of the repeated prisoners’ dilemma, in which each player is required to play using a Moore machine (a type of finite state transducer). Rubinstein and Abreu [
15] investigated the case of infinitely repeated games. They used the Nash equilibrium as a solution concept, where players seek to maximize their profit and minimize the complexity of their strategies. Inspired by the Abreu – Rubinstein style systems, Binmore and Samuelson [
16] replaced the solution concept of Nash equilibrium with that of the evolutionarily stable strategy. They showed that such automata are efficient in the sense that they maximize the sum of the payoffs. Ben-Porath [
17] studied repeated games and the behavior of equilibrium payoffs for players using bounded complexity strategies. The strategy complexity is measured in terms of the state size of the minimal automaton that can implement it. They observed that when the size of the automata of both players tends to infinity, the sequence of values converges to a particular value for each game. Marks [
18] also studied repeated games with the assistance of finite automata.
An important work in the field of quantum game theory by Eisert et al. [
19] examined the application of quantum techniques in the prisoners’ dilemma game. Their work was later debated by others, such as Benjamin and Hayden in [
20] and Zhang in [
21], where it was pointed out that players in the game setting of [
19] were restricted and therefore the resulting Nash equilibria were not correct. The work in [
22] gave an elegant introduction to quantum game theory, along with a review of the relevant literature for the first years of this newborn field. Parrondo games and quantum algorithms were discussed in [
23]. The relation between Parrondo games and a type of automata, specifically quantum lattice gas automata, was the topic of [
24]. Bertelle et al. [
25] examined the use of probabilistic automata, evolved from a genetic algorithm, for modeling adaptive behavior in the prisoners’ dilemma game. Piotrowski et al. [
26] provided a historic account and outlined the basic ideas behind the recent development of quantum game theory. They also gave their assessment about possible future developments in this field and their impact on information processing. Recently, Suwais [
27] examined different types of automata variants and reviewed the use for each one of them in game theory. In a similar vein, Almanasra et al. [
28] reported that finite automata are suitable for simple strategies whereas adaptive and cellular automata can be applied in complex environments.
Variants of quantum finite automata, placing emphasis on hybrid models, were presented in [
29] by Li and Feng, where they obtained interesting theoretical results demonstrating the advantages of these models. The use of such finite state machines for the representation of quantum games could, perhaps, constitute an alternative to classical automata, particularly in view of some encouraging results regarding their power and expressiveness (see [
30,
31,
32]).
The relation of quantum games with finite automata was also studied in [
33]. In that work, quantum automata accepting infinite words were associated with winning strategies for abstract quantum games. The current paper differs from [
33] in the following aspects: (i) the focus is in the
penny flip game and all its variations; (ii) the automata are either deterministic or nondeterministic finite automata; and (iii) the words accepted by the automata correspond to moves by both players.
4. Games and Words
In this work, we intend to examine all finite games that can be played between Picard and Q. These games are in a sense “similar” to the original game and can, therefore, be viewed as extensions that arise from modifications of the rules of the original game. First we must precisely state what we shall keep from the game. Our analysis will be based on the following four hypotheses.
Hypothesis 1. (H1) The two players, Picard and Q, are the stars of the game. Thus, they will continue to play against each other in all the two-persons games we study. Although the games will be finite, their duration will vary. Most importantly, the pattern of the games will vary: Picard may make the first move, one player may act on the coin for a number of consecutive rounds while the other player stays idle, and so on.
Hypothesis 2. (H2) The other cornerstone of the game is the two-dimensional coin, so the players will still act on the same coin. This means that our games take place in the two-dimensional complex Hilbert space and we shall not be concerned with higher dimensional analogs of the game like those in [6,7]. Hypothesis 3. (H3) Let us agree that the players have exactly the same actions at their disposal, that is Picard can use either I or F, and Q can use H. This will enable us to treat all games in a uniform manner by using the same alphabet and notation.
At this point, it is perhaps expedient to clarify why we have presumed that Q’s repertoire is limited to H. One of the fundamental assumptions of game theory is that the players are rational. This means that they always act so as to maximize their payoff (see references [2,3] for a more in depth analysis). Rationality will force each player to choose the best action from a set of possible actions. In this case, Q, being a quantum entity, can choose his actions from the infinite set of unitary operators (technically from the group). For instance, Q is allowed to use I, F, something like , etc. Nonetheless, Q will discard such choices and will eventually play a dominant strategy such as H, followed by H, as his rationality demands. It is this line of thought that has led us to assume that Q has just one action, namely H. Hypothesis 4. (H4) Finally, we assume that the coin can initially be at one of the two basic states (the coin is placed heads up) or (the coin is placed tails up), and this state is known to both players. We note that, for each game that begins with the coin in state , there exists an analogous game that begins with the coin in state and vice versa. When the game is over, the state of the coin is measured in the orthonormal basis , and, if it is found to be in the initial basic state, Q wins; otherwise, Picard wins. This settles the question of how the winner is determined.
From now on, we shall take for granted the hypotheses H1–H4 without any further mention.
Let N be the set of the two players and let be the set of all finite sequences over N. We agree that contains the empty sequence e. Each is called a sequence of moves because it encodes a game between Picard and Q. For instance the sequence expresses the original game, while the sequence represents a five-round game variant, where Picard moves during Rounds 1, 3 and 5, and Q during Rounds 2 and 4. This idea is formalized in the next definition.
Definition 3. Each sequence of moves defines the finite game between Picard and Q. The rules of are:
The initial state of the coin is . In view of hypothesis H4, is either or .
If , then is the 0-round trivial game (neither Picard nor Q act on the coin, which remains at its initial state).
If , where , , then is a game that lasts n rounds and determines which of the two players moves during round i. Specifically, if then it is Picard’s turn to act on the coin, whereas if then it is Q’s turn to act on the coin.
In this work, we shall employ sequences of moves as a precise, unambiguous and succinct way for defining finite games between Picard and Q. For instance, the move sequences (Picard, Picard, Q, Q, Picard, Picard) and (Picard, Q, Picard, Q, Picard, Q, Picard, Q, Picard) correspond to a six-round and a nine-round game, respectively. These particular games will be used in
Section 7.
Considering that the actions of Picard and Q are just three, namely and H, we define the set of actions . The set of all finite sequences of actions, which includes the empty sequence , is denoted by . In the original game, there are just two possible such sequences: and . Each action sequence is meaningful only in the appropriate game. For example, the following sequence is unsuitable for the game, but it makes perfect sense in a four-round game where Picard plays during the first and fourth round and Q plays during the second and third round. The precise game for which a given sequence of actions is appropriate is defined below.
Definition 4. The function , which maps sequences of actions to sequences of moves, is defined as follows.
- 1.
, and
- 2.
If , , , then , where if or and if .
Every action sequence, α is an admissible sequence for the underlying game .
If Q (Picard) wins the game with the admissible sequence α with probability , we say that Q (Picard) surely wins with α, or that α is a winning sequence for Q (Picard) in .
We employ the notation , respectively , as an abbreviation of the foregoing assertion.
It is evident that is not an injective function. Take for example and ; both correspond to the same sequence of moves . It is also clear that only admissible sequences are meaningful.
In this work, we shall examine several variants of the game. To each one, we shall associate an automaton and study the language it accepts. As it will turn out, in every case the corresponding language has the same characteristic property. Automata are simple but fundamental models of computation. They recognize regular languages of words from a given alphabet . The set of all finite words over is denoted by ; we recall that contains the empty word . The operation of the automaton is very simple: starting from its start state the automaton reads a word w and ends up in a certain state. It accepts (or recognizes) w if and only if this final state belongs to the set of accept states. The set of all the words that are accepted by the automaton is the language recognized (or accepted) by the automaton. We follow the convention of denoting by the language recognized by the automaton A.
To associate games with automata in a productive way, we must fix an appropriate alphabet
and map the actions of the players to the letters of
. Accordingly, the alphabet
must also contain tree letters.
Table 1 shows the 1-1 correspondence between the operators
and
H and the letters of the alphabet
. In this work, we are interested only in finite games and, hence, in finite words and finite sequences of actions. For simplicity, we shall omit the adjective finite from now and simply write game, word and sequence of actions.
Definition 5. Given the set of actions of Picard and Q, the corresponding alphabet is .
We define the letter assignment function and the operator assignment function .
- 1.
, ;
- 2.
, ; and
- 3.
, .
The letter assignment function follows the obvious mnemonic rule of mapping each operator, which in the literature is typically denoted by an uppercase letter, to the same lowercase letter. Clearly, is the inverse of . All the automata we shall encounter share the same alphabet .
Now, via , we can map finite sequences of actions to words and via we can map words to finite sequences of actions. For instance, the sequence is mapped to , the sequence is mapped to , etc. In this fashion, every sequence of actions is mapped to a word . But, this is a two-way street, meaning that each word from corresponds to a sequence of actions: corresponds to .
At this point, we should clarify that, in the rest of this paper, action sequences will be written as comma-delimited lists of actions enclosed within a pair of left and right parenthesis. This is in accordance with the practice we have followed so far, e.g., when referring to the action sequences , or . On the other hand, words, despite also being considered as sequences of symbols from the alphabet , are always written as a simple concatenation of symbols, such as , or , and never , etc. In this work, we shall adhere to this well-established tradition.
Formally, this correspondence between action sequences and words is achieved by properly extending and .
Definition 6. The word mapping and the action sequence mapping are defined recursively as follows.
- 1.
, , and
- 2.
For every , every , every , and every :
, .
Moreover, a word via the corresponding sequence of actions can be thought of as describing the game . For example, the word corresponds to a five-round game, where Q plays only during Rounds 1 and 5, whereas Picard gets to act on the coin during the consecutive Rounds 2, 3 and 4.
5. An Automaton for the PQ Game
As we have explained in previous sections, the coin in the
game is a two-dimensional system and so its state can be described by a normalized ket
. The players act upon the coin via the unitary operators
and
H whose matrix representation is given in Equation (
3).
The game proceeds as follows:
The initial state of the coin is .
After Q’s first move (which is an action on the coin by
H), the coin enters state
. We call this state
(see
Figure 1 and
Table 2).
is a very special state in the sense that no matter what Picard chooses to play (Picard can act either by I or by F), after his move the coin remains in the state .
Finally, Q wins the game by applying H one last time, which in effect sends the coin back to its initial state .
The simple automaton
shown in
Figure 1 expresses concisely the states of the coin and the effect of the actions of the two players. The states of the automaton are in 1-1 correspondence with the states the coin goes through during the game (see
Table 2). The actions of the players, that is the unitary operators
, are in 1-1 correspondence with the alphabet
of
(see
Table 1).
The effect of the actions of the players upon the coin is captured by the transitions between the states. Technically,
is a nondeterministic automaton (see [
35]) that has only two states:
and
, where
is the start and the unique accept state. The nondeterministic nature of
stems from the fact that no outgoing transitions from
are labeled with
i or
f. This is a feature, not a bug, because the rules of the game stipulate that Q makes the first move and Picard’s only move takes place when the coin is in state
. This means that Picard never gets a chance to act when the coin is in state
. Hence,
is specifically designed so that the only possible action while in state
is by Q via
H. This will have an effect on the words accepted by
, as will be explained below. Other than this subtle point, the behavior of
can be considered deterministic.
According to the rules of the game, there are just two admissible sequences of actions: and . Both of them guarantee that Q will win with probability 1.0. The corresponding words are: and , both of which are accepted by and, thus, belong to . Formally, these two words are the only ones that correspond to valid game moves.
Let us now take a step back and view
as a standalone automaton. Its language
can be succinctly described by the regular expression
(for more about regular expressions we refer again to [
35]). Thus,
contains an infinite number of words, but only two, namely
and
, correspond to admissible sequences of game actions. What about the other words of
?
Even though the fact that the other words of do not correspond to permissible sequences of moves for the original game, they do share a very interesting property. Given an arbitrary word , consider the game . If the sequence of actions is played, then Q will surely win, that is Q will win with probability . Note that , in general, will contain actions by both players. We emphasize that this property holds for every word of . To develop a better understanding of this characteristic property, let us look at some concrete examples.
The empty word that technically belongs to can be viewed as the representation of the trivial game, where no player gets to act on the coin, so the coin stays at its initial state and Q trivially wins.
Words such as and , i.e., having the form , correspond to the most unfair (for Picard) games, where the game lasts exactly rounds, for some , and Q moves during each round (Picard does not get to make any move at all).
Words of the form , where , represent games that last rounds. In these games, Q plays only during the first and last round of the game, whereas Picard plays during the n intermediate rounds. These variants give to Picard the illusion of fairness, without changing the final outcome.
Words of the form , e.g., , correspond to more complex games. They are in effect independent repetitions of the previous category of games.
The formal definition of “winning” automata will be given in
Section 7. The idea is very simple: a winning automaton for Q (Picard) accepts a word
w only if Q (respectively Picard) surely wins the game
with
, where
s is the initial state of the automaton,
is the corresponding action sequence, and
is the corresponding move sequence. Therefore, a winning automaton for one of the players does not accept a single word for which, in the corresponding game, the associated sequence of actions will result in the other player winning with nonzero probability, for instance with probability
or
.
7. Automata Capturing Sets of Games
In this section, we shall prove that is a “better”, more “complete” representation of the finite games between Picard and Q compared to all the previous automata. As a matter of fact, in a precise sense captures all the finite games between Picard and Q.
We begin by giving the formal definition of winning automaton.
Definition 7 (Winning automaton)
. Consider an automaton A with initial state s, where s is either or . Let be a word accepted by A, let be the corresponding sequence of actions, and let be the corresponding sequence of moves.
If for every word w accepted by A, Q surely wins in the game with , then A is a winning automaton for Q.
Symmetrically, A is a winning automaton for Picard, if for each word w accepted by A, Picard surely wins in the game with .
A more succinct way to express that
A is a winning automaton for Q or Picard would be to write
respectively.
First, we consider
all finite games between Picard and Q that satisfy the following conditions (recall the hypotheses at the beginning of
Section 4):
Picard’s actions are either I or F and Q’s action is H.
The coin is initially at state .
Q wins if, when the game is over and the state of the coin is measured, it is found to be in state ; otherwise, Picard wins.
The proofs of the main results of this section are easy but lengthy, so they are given in the
Appendix A.
Theorem 1 (Winning automata for Q)
. The automata , , , and are all winning automata for Q.
Definition 8 (Complete automaton for winning sequences)
. An automaton A with initial state s (s is either or ) is complete with respect to the winning sequences for Q if for every finite game between Picard and Q in which the coin is initially at state , every sequence of actions that enables Q to win the game with probability corresponds to a word accepted by A.
Symmetrically, A is complete with respect to the winning sequences for Picard, if for every finite game between Picard and Q and for every sequence of actions that enables Picard to win with probability , the corresponding word is accepted by A.
More formally, the completeness property can be expressed as follows
Theorem 2 (Complete automaton for Q)
. is complete with respect to the winning sequences for Q.
To appreciate the importance of the completeness property, we point out that is not complete for Q. Let us first consider the six-round game (Picard, Picard, Q, Q, Picard, Picard). In this game, Q surely wins if the action sequence is played. The corresponding word is , which belongs to but not to . Thus, fails to accept all winning sequences for Q, i.e., it is not complete in this respect. This counterexample demonstrates that fails to be complete for Q.
7.1. Devising Other Variants
We can be even more flexible by using the semiautomaton
A shown in
Figure 5. Technically,
A is not an automaton because no initial state and no final states are specified. However,
A captures the essence of all games between Picard and Q because it can serve as a template for automata that correspond to games that satisfy specific properties. This is easily seen by considering the examples that follow. Recall that we always operate under the assumption that Q wins if, when the game is over and the state of the coin is measured, it is found to be in the
initial state; otherwise Picard wins.
7.1.1. Changing the Initial State of the Coin
Suppose we want to construct a
complete winning automaton for Q for all the games in which the coin is initially at state
. Starting from the semiautomaton
A of
Figure 5 we define
The resulting automaton
is depicted in
Figure 6. The following theorem holds for
.
Theorem 3 (Complete and winning automaton II for Q)
. is a complete and winning automaton for Q for all the games in which the initial state of the coin is .
7.1.2. Picard Surely Wins
By suitably modifying the semiautomaton A, we can also design a complete winning automaton for Picard for all the games in which the coin is initially at state . We can do that by
This will result in the automaton
depicted in
Figure 7, for which one can easily prove the next theorem.
Theorem 4 (Complete and winning automaton for Picard)
. is a complete and winning automaton for Picard for all the games in which the initial state of the coin is .
Similarly, we can define a complete winning automaton for Picard for all the games in which the coin is initially at state . All we have to do is
This will result in the automaton
shown in
Figure 8, for which one can easily show that the following theorem holds.
Theorem 5 (Complete and winning automaton II for Picard)
. is a complete and winning automaton for Picard for all the games in which the initial state of the coin is .
7.1.3. Fair Games
Up to this point, we have focused on winning action sequences for Q or Picard, that is sequences for which Q or Picard, respectively, wins the game with probability . However, we can also capture action sequences for which both players have equal probability to win the game. We call such sequences fair.
Definition 9. Let α be an admissible sequence for the underlying game . If both Q and Picard have equal probability to win the game using α, we say that α is a fair sequence for Q and Picard in .
An automaton A with initial state s (s is either or ) is complete with respect to the fair sequences if for every finite game between Picard and Q in which the coin is initially at state , every fair sequence corresponds to a word accepted by A.
The semiautomaton
A of
Figure 5 can help in this case too. The states
and
of
A correspond to the states
and
of the coin, respectively, as can be seen in
Table 2. These states share a common characteristic: if the coin ends up in any of them, then, after the measurement in the orthonormal basis
, the state of the coin will either be the basic ket
with probability
, or the basic ket
with equal probability
. Hence, if the coin ends up in these states, then both Q and Picard have equal probability
to win. Therefore, we can design an automaton that accepts
all the fair sequences for all the games in which the coin is initially at state
by
Symmetrically, we can define an automaton that accepts all the fair sequences for all the games in which the coin is initially at state by
The resulting automata are
and
, shown in
Figure 9 and
Figure 10, respectively.
Theorem 6 (Complete automata for fair sequences)
. and are complete for fair sequences, that is they accept all fair sequences for all the games in which the initial state of the coin is and , respectively.
8. Conclusions and Further Work
Quantum technologies have attracted the interest of not only the academic community but also of the industry. This has led to further research on the relationship between classical and quantum computation. Standard and well-established notions and systems have to be examined and, if necessary, revised in the light of the upcoming quantum era.
In this work, we have presented a way to construct automata, and a semiautomaton, from the game, such that the resulting automata and semiautomaton capture, in a specific sense, every conceivable variation and extension of the game. That is, the automata can be used to study possible variants of the game, and their accepting language can be used to determine strategies for any player, dominant or otherwise. Specifically, starting from the automaton that corresponds to the standard game, we construct automata for various interesting variations of the game, before finally presenting a semiautomaton that is in a sense “complete” with regard to the game and captures the “essence” of the generalized game. This simply means that, by providing appropriate initial and final states for the semiautomaton, we can study any possible variation of the game.
We remark that the automata presented here do much more than accepting
dominant strategies. In game theory a strategy
i for a player is
strongly dominated by strategy
j if the player’s payoff from
i is strictly less than that from
j. A strategy
i for a player is a
strongly dominant strategy iff all other strategies for this player are strongly dominated by
i (see [
1,
2] for details). In our context, the strategy
for the original
game is a strongly dominant strategy for Q. The automata we have constructed accept sequences of actions by both players, i.e., sequences that contain the actions of both players. As we have explained in
Section 7, they can be designed so as to accept all action sequences of all possible games between Picard and Q for which either Q surely wins, or Picard surely wins or even they both have probability
to win.
We believe that the current methodology can be easily extended to account for greater variation in the actions of Picard and Q. Our analysis was based on the premise that the set of actions is precisely . This set can be augmented by adding a finite number of actions, as long as these actions represent rotations through an angle about the origin and reflections about a line through the origin that makes an angle with the positive x-axis, where and , where are positive integers. In that way, Q, being the quantum player, would have many more actions in his disposal, rather than only H. However, more actions may not necessarily mean more winning strategies for Q. Obviously, in such a case, the resulting finite automata would have more states that the automata presented in this paper.
Future directions for this work are numerous, including the construction of automata expressing other quantum games, and the application of automata-theoretic notions to such games. The connection of standard finite automata with the players actions on a particular quantum game can only be seen as a first step in the direction of checking, not only other games, but also different game modes on already known setups.