Multiplayer Cost Games with Simple Nash Equilibria

Multiplayer games with selfish agents naturally occur in the design of distributed and embedded systems. As the goals of selfish agents are usually neither equivalent nor antagonistic to each other, such games are non zero-sum games. We study such games and show that a large class of these games, including games where the individual objectives are mean- or discounted-payoff, or quantitative reachability, and show that they do not only have a solution, but a simple solution. We establish the existence of Nash equilibria that are composed of k memoryless strategies for each agent in a setting with k agents, one main and k-1 minor strategies. The main strategy describes what happens when all agents comply, whereas the minor strategies ensure that all other agents immediately start to co-operate against the agent who first deviates from the plan. This simplicity is important, as rational agents are an idealisation. Realistically, agents have to decide on their moves with very limited resources, and complicated strategies that require exponential--or even non-elementary--implementations cannot realistically be implemented. The existence of simple strategies that we prove in this paper therefore holds a promise of implementability.Comment: 23 page

Repairing Multi-Player Games

Synthesis is the automated construction of systems from their specifications. Modern systems often consist of interacting components, each having its own objective. The interaction among the components is modeled by a multi-player game. Strategies of the components induce a trace in the game, and the objective of each component is to force the game into a trace that satisfies its specification. This is modeled by augmenting the game with omega-regular winning conditions. Unlike traditional synthesis games, which are zero-sum, here the objectives of the components do not necessarily contradict each other. Accordingly, typical questions about these games concern their stability - whether the players reach an equilibrium, and their social welfare - maximizing the set of (possibly weighted) specifications that are satisfied. We introduce and study repair of multi-player games. Given a game, we study the possibility of modifying the objectives of the players in order to obtain stability or to improve the social welfare. Specifically, we solve the problem of modifying the winning conditions in a given concurrent multi-player game in a way that guarantees the existence of a Nash equilibrium. Each modification has a value, reflecting both the cost of strengthening or weakening the underlying specifications, as well as the benefit of satisfying specifications in the obtained equilibrium. We seek optimal modifications, and we study the problem for various omega-regular objectives and various cost and benefit functions. We analyze the complexity of the problem in the general setting as well as in one with a fixed number of players. We also study two additional types of repair, namely redirection of transitions and control of a subset of the players

The Complexity of Nash Equilibria in Limit-Average Games

We study the computational complexity of Nash equilibria in concurrent games with limit-average objectives. In particular, we prove that the existence of a Nash equilibrium in randomised strategies is undecidable, while the existence of a Nash equilibrium in pure strategies is decidable, even if we put a constraint on the payoff of the equilibrium. Our undecidability result holds even for a restricted class of concurrent games, where nonzero rewards occur only on terminal states. Moreover, we show that the constrained existence problem is undecidable not only for concurrent games but for turn-based games with the same restriction on rewards. Finally, we prove that the constrained existence problem for Nash equilibria in (pure or randomised) stationary strategies is decidable and analyse its complexity.Comment: 34 page

LIPIcs

Network games are widely used as a model for selfish resource-allocation problems. In the classicalmodel, each player selects a path connecting her source and target vertices. The cost of traversingan edge depends on theload; namely, number of players that traverse it. Thus, it abstracts the factthat different users may use a resource at different times and for different durations, which playsan important role in determining the costs of the users in reality. For example, when transmittingpackets in a communication network, routing traffic in a road network, or processing a task in aproduction system, actual sharing and congestion of resources crucially depends on time.In [13], we introducedtimed network games, which add a time component to network games.Each vertexvin the network is associated with a cost function, mapping the load onvto theprice that a player pays for staying invfor one time unit with this load. Each edge in thenetwork is guarded by the time intervals in which it can be traversed, which forces the players tospend time in the vertices. In this work we significantly extend the way time can be referred toin timed network games. In the model we study, the network is equipped withclocks, and, as intimed automata, edges are guarded by constraints on the values of the clocks, and their traversalmay involve a reset of some clocks. We argue that the stronger model captures many realisticnetworks. The addition of clocks breaks the techniques we developed in [13] and we developnew techniques in order to show that positive results on classic network games carry over to thestronger timed setting

LIPIcs

Network games are widely used as a model for selfish resource-allocation problems. In the classicalmodel, each player selects a path connecting her source and target vertices. The cost of traversingan edge depends on theload; namely, number of players that traverse it. Thus, it abstracts the factthat different users may use a resource at different times and for different durations, which playsan important role in determining the costs of the users in reality. For example, when transmittingpackets in a communication network, routing traffic in a road network, or processing a task in aproduction system, actual sharing and congestion of resources crucially depends on time.In [13], we introducedtimed network games, which add a time component to network games.Each vertexvin the network is associated with a cost function, mapping the load onvto theprice that a player pays for staying invfor one time unit with this load. Each edge in thenetwork is guarded by the time intervals in which it can be traversed, which forces the players tospend time in the vertices. In this work we significantly extend the way time can be referred toin timed network games. In the model we study, the network is equipped withclocks, and, as intimed automata, edges are guarded by constraints on the values of the clocks, and their traversalmay involve a reset of some clocks. We argue that the stronger model captures many realisticnetworks. The addition of clocks breaks the techniques we developed in [13] and we developnew techniques in order to show that positive results on classic network games carry over to thestronger timed setting

Infinite-Duration Bidding Games

Two-player games on graphs are widely studied in formal methods as they model the interaction between a system and its environment. The game is played by moving a token throughout a graph to produce an infinite path. There are several common modes to determine how the players move the token through the graph; e.g., in turn-based games the players alternate turns in moving the token. We study the {\em bidding} mode of moving the token, which, to the best of our knowledge, has never been studied in infinite-duration games. The following bidding rule was previously defined and called Richman bidding. Both players have separate {\em budgets}, which sum up to $1$. In each turn, a bidding takes place: Both players submit bids simultaneously, where a bid is legal if it does not exceed the available budget, and the higher bidder pays his bid to the other player and moves the token. The central question studied in bidding games is a necessary and sufficient initial budget for winning the game: a {\em threshold} budget in a vertex is a value $t \in [0,1]$ such that if Player $1$'s budget exceeds $t$, he can win the game, and if Player $2$'s budget exceeds $1-t$, he can win the game. Threshold budgets were previously shown to exist in every vertex of a reachability game, which have an interesting connection with {\em random-turn} games -- a sub-class of simple stochastic games in which the player who moves is chosen randomly. We show the existence of threshold budgets for a qualitative class of infinite-duration games, namely parity games, and a quantitative class, namely mean-payoff games. The key component of the proof is a quantitative solution to strongly-connected mean-payoff bidding games in which we extend the connection with random-turn games to these games, and construct explicit optimal strategies for both players.Comment: A short version appeared in CONCUR 2017. The paper is accepted to JAC