Abstract
In this invited contribution, we propose a comprehensive introduction to game theory applied in computer aided synthesis. In this context, we give some classical results on two-player zero-sum games and then on multi-player non zero-sum games. The simple case of one-player games is strongly related to automata theory on infinite words. All along the article, we focus on general approaches to solve the studied problems, and we provide several illustrative examples as well as intuitions on the proofs.
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Notes
- 1.
This condition guarantees that there is no deadlock. It can be assumed w.l.o.g. for all the problems considered in this article.
- 2.
We also say that player i controls the vertices of \(V_i\).
- 3.
that is, an irreflexive, transitive and total binary relation.
- 4.
In all examples of this article, circle (resp. square) vertices are controlled by player 1 (resp. player 2).
- 5.
This informal definition is enough for this survey. See for instance [38] for a definition.
- 6.
As player 1 can only loop on vertices \(v_2\) and \(v_3\), we do not formally define \(\sigma _1\) on histories ending with \(v_2\) or \(v_3\).
- 7.
This problem is focused on Player 1, the payoff function \(f_2\) and preference relation \(\prec _2\) of Player 2 do not matter.
- 8.
Alternatively, \(\prec _i\) can be the ordering > meaning that player i prefers to minimize the payoff of a play.
- 9.
A colored variant of Muller objective is defined from a coloring \(c~: V \rightarrow \mathbb N\) of the vertices: the family \(\mathcal F\) is composed of subsets of \(c(V)\) (instead of V) and \(\varOmega _i = \{\rho \in Plays\mid inf(c(\rho _0)c(\rho _1)\ldots ) \in \mathcal{F} \}\) [39]. See [42] for several variants of Muller games.
- 10.
In Sect. 3.1, we omit index 1 everywhere since player 1 is the unique player of the game.
- 11.
The hypotheses of this theorem are those given in the full version of [36] available at http://www.labri.fr/perso/gimbert/.
- 12.
- 13.
- 14.
- 15.
This tuple of payoff functions is used by player 1 contrarily to Definition 2 where function \(f_i\) is used by player i for all \(i \in \varPi \).
- 16.
We found no reference for this result. The PSPACE membership (resp. the finite memory of the strategies) follows from [1] (resp. [13]). In [1], games with a union of a Streett objective and a Rabin objective are shown to be PSPACE-hard. It is thus also the case for games with a union of Streett objectives. By Martin’s theorem, it follows that games with an intersection of Rabin objectives are PSPACE-hard.
- 17.
Recall that the payoff function and the preference relation of the second player do not matter in two-player zero-sum games.
- 18.
In [12], one hypothesis is missing: the required optimal strategies must be uniform.
- 19.
- 20.
Recall our comment after Theorem 22.
- 21.
The reduction is given for another kind of solution profile but it also works for NEs.
- 22.
The definition was given for player 1.
- 23.
A restriction to two-player games is necessary to deal with a secure preference that is total.
- 24.
In this particular context, plays are finite paths.
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Acknowledgments
We would like to thank Patricia Bouyer, Thomas Brihaye, Emmanuel Filiot, Hugo Gimbert, Quentin Hautem, Mickaël Randour, and Jean-François Raskin for their useful discussions and comments that helped us to improve the presentation of this article.
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Appendix
Appendix
In this appendix, we give a sketch of proof for Muller games in Theorem 31. Recall that each player i has the objective \(\varOmega _i = \{\rho \in Plays\mid inf(\rho ) \in \mathcal{F}_i \}\) with \(\mathcal{F}_i \subseteq 2^V\), and that the values \(val_i(v)\), \(v \in V\), in each game \(G_i\) can be computed in polynomial time (Theorem 21). To prove P membership for the constraint problem with bounds \((\mu _i)_{i \in \varPi }, (\nu _i)_{i \in \varPi }\), we apply the approach (3). Notice that for the required play \(\rho \in Plays(v_0)\) in (3), the set \(U = inf(\rho )\) must be a strongly connected component that is reachable from the initial vertex \(v_0\). Moreover if for some i, \(f_i(\rho ) = 0\) then \({val}_i(\rho _k) = 0\) for all \(\rho _k \in V_i\), and if \(\nu _i = 0\), then \(f_i(\rho ) = 0\). We thus proceed as follows. (i) For each i such that \(\nu _i = 1\), for each \(U \in \mathcal{F}_i\) (seen as a potential \(U = inf(\rho )\)), the following computations are done in polynomial time for all \(j\in \varPi \):
-
if \(\mu _j = 1\) ((3) imposes \(f_j(\rho ) = 1\)), test whether \(U \in \mathcal{F}_j\),
-
if \(\nu _j = 0\) ((3) imposes \(f_j(\rho ) = 0\)), test whether \(U \not \in \mathcal{F}_j\) and whether each \(v \in U \cap V_j\) has value \({val}_j(v) = 0\),
-
if \(\mu _j = 0\) and \(\nu _j = 1\) ((3) allows either \(f_j(\rho ) = 0\) or \(f_j(\rho ) = 1\)), then if \(U \not \in \mathcal{F}_j\), test whether each \(v \in U \cap V_j\) has value \({val}_j(v) = 0\).
Finally, construct in polynomial time the game \(G'\) from G such that each \(V_j\) is limited to \(\{v \in V_j \mid {val}_j(v) = 0 \}\) whenever \(U \not \in \mathcal{F}_j\), and test whether U is a strongly connected component that is reachable from \(v_0\) in \(G'\). As soon as this sequence of tests is positive, there exists \(\rho \) satisfying (3). (ii) It may happen that step (i) cannot be applied (because there is no j such that \(\mu _j = 1\), and for j such that \(\mu _j = 0\) and \(\nu _j = 1\), there is no potential \(U = inf(\rho )\)). In this case, we construct in polynomial time a two-player game \(G'\) from G such that each \(V_i\) is limited to \(\{v \in V_i \mid {val}_i(v) = 0 \}\), player 1 controls no vertex and player 2 is formed by the coalition of all \(i \in \varPi \), and the objective is a Muller objective with \(\mathcal{F} = \cup _{i\in \varPi } \mathcal{F}_i\). We then test in polynomial time whether player 1 has no winning strategy from \(v_0\) in this Muller game.
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Bruyère, V. (2017). Computer Aided Synthesis: A Game-Theoretic Approach. In: Charlier, É., Leroy, J., Rigo, M. (eds) Developments in Language Theory. DLT 2017. Lecture Notes in Computer Science(), vol 10396. Springer, Cham. https://doi.org/10.1007/978-3-319-62809-7_1
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