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Florian Horn

Publications and source records attributed to Florian Horn.

16 recordsLinked to original sources
arXiv2026

Generalised Reachability Games

We study two-player zero-sum turn-based games played on graphs with multiple reachability objectives called generalised reachability games. In classic reachability games the goal of one player, Eve, is to visit a given target set of vertices, and that of the other player, Adam, is to prevent this. In generalised reachability games, the single target set is replaced with a family of target sets and the objective of Eve is to visit all of them in any order. We study the complexity of deciding the winner in two-player games with generalised reachability objectives. Our study reveals that an important parameter that determines the complexity of this problem is the size of the target sets. We first prove that deciding the winner in such games is PSPACE-complete, and the PSPACE lower bound holds even when the size of each target set is at most three. By contrast, we show that the problem is FPT in the number of target sets of size greater than one. Moreover, we consider the memory requirements for both players and give matching upper and lower bounds on the sizes of winning strategies. We also study optimisation variants of these games. For the optimisation problems, we show intractability for most interesting cases. Particularly, in contrast to the tractability of generalised reachability in the case with singleton target sets, the optimisation problem is coNP-hard when Eve tries to maximise the number of target sets that are visited. Tractability of this case can be recovered in a different optimisation setting where Eve is required to pledge a maximum sized subset of target sets that she can guarantee to visit.

cs.GT↗
arXiv2025

Games on Graphs: From Logic and Automata to Algorithms

The objective of this book is to give a comprehensive presentation of the research field concerned with infinite duration games on graphs. Historically, these game models appeared in the study of automata and logic, and they later became important for program verification and synthesis. They have many more applications, in particular some of the models investigated in this book were introduced and studied in neighbouring research communities such as optimisation, reinforcement learning, model theory, and set theory.

cs.GT↗
arXiv2025

On the Complexity of the Optimal Correlated Equilibria in Extensive-Form Games

A major open question in algorithmic game theory is whether normal-form correlated equilibria (NFCE) can be computed efficiently in succinct games such as extensive-form games. Motivated by this question, we study the associated Threshold problem: deciding whether there exists a correlated equilibrium whose value exceeds a given threshold. We prove that this problem is PSPACE-hard for NFCE in multiplayer extensive-form games with perfect recall, even for fixed thresholds. To contextualize this result, we also establish the complexity of the Threshold problem for Nash equilibria in this setting, showing it is ER-complete. These results uncover a surprising complexity reversal: while optimal correlated equilibria are computationally simpler than optimal Nash in normal-form games, the opposite holds in extensive-form games, where computing optimal correlated equilibria is strictly harder unless ER is equal to PSPACE. We also address a related question by von Stengel and Forges, who introduced the notions of extensive-form correlated equilibrium (EFCE) and agent-form correlated equilibrium (AFCE). They asked how difficult the Threshold problem is for AFCE; we answer this question by proving that it is NP-hard, even in two-player games without chance nodes. Complementing our hardness results, we establish tight complexity classifications for the Threshold problem across several correlated equilibrium concepts - including EFCE, AFCE, normal-form coarse, extensive-form coarse, and agent-form coarse correlated equilibria. For each of these solution concepts in multiplayer stochastic extensive-form games with perfect recall, we prove NP-completeness by providing matching NP upper bounds to the previously known hardness results. Finally, we also place the problem of computing arbitrary Nash Equilibria in extensive-form games in FixP, matching its complexity in normal-form games.

cs.GT↗
arXiv2024

Revelations: A Decidable Class of POMDPs with Omega-Regular Objectives

Partially observable Markov decision processes (POMDPs) form a prominent model for uncertainty in sequential decision making. We are interested in constructing algorithms with theoretical guarantees to determine whether the agent has a strategy ensuring a given specification with probability 1. This well-studied problem is known to be undecidable already for very simple omega-regular objectives, because of the difficulty of reasoning on uncertain events. We introduce a revelation mechanism which restricts information loss by requiring that almost surely the agent has eventually full information of the current state. Our main technical results are to construct exact algorithms for two classes of POMDPs called weakly and strongly revealing. Importantly, the decidable cases reduce to the analysis of a finite belief-support Markov decision process. This yields a conceptually simple and exact algorithm for a large class of POMDPs.

cs.AI↗
arXiv2024

Playing Safe, Ten Years Later

We consider two-player games over graphs and give tight bounds on the memory size of strategies ensuring safety objectives. More specifically, we show that the minimal number of memory states of a strategy ensuring a safety objective is given by the size of the maximal antichain of left quotients with respect to language inclusion. This result holds for all safety objectives without any regularity assumptions. We give several applications of this general principle. In particular, we characterize the exact memory requirements for the opponent in generalized reachability games, and we prove the existence of positional strategies in games with counters.

cs.GT↗
arXiv2020

Deciding the existence of cut-off in parameterized rendez-vous networks

We study networks of processes which all execute the same finite-state protocol and communicate thanks to a rendez-vous mechanism. Given a protocol, we are interested in checking whether there exists a number, called a cut-off, such that in any networks with a bigger number of participants, there is an execution where all the entities end in some final states. We provide decidability and complexity results of this problem under various assumptions, such as absence/presence of a leader or symmetric/asymmetric rendez-vous.

cs.LO↗
arXiv2017

Trading Bounds for Memory in Games with Counters

We study two-player games with counters, where the objective of the first player is that the counter values remain bounded. We investigate the existence of a trade-off between the size of the memory and the bound achieved on the counters, which has been conjectured by Colcombet and Loeding. We show that unfortunately this conjecture does not hold: there is no trade-off between bounds and memory, even for finite arenas. On the positive side, we prove the existence of a trade-off for the special case of thin tree arenas. This allows to extend the theory of regular cost functions over thin trees, and obtain as a corollary the decidability of cost monadic second-order logic over thin trees.

cs.FL↗
arXiv2017

Two Recursively Inseparable Problems for Probabilistic Automata

This paper introduces and investigates decision problems for numberless probabilistic automata, i.e. probabilistic automata where the support of each probabilistic transitions is specified, but the exact values of the probabilities are not. A numberless probabilistic automaton can be instantiated into a probabilistic automaton by specifying the exact values of the non-zero probabilistic transitions. We show that the two following properties of numberless probabilistic automata are recursively inseparable: - all instances of the numberless automaton have value 1, - no instance of the numberless automaton has value 1.

cs.FL↗
arXiv2015

Entropy Games and Matrix Multiplication Games

Two intimately related new classes of games are introduced and studied: entropy games (EGs) and matrix multiplication games (MMGs). An EG is played on a finite arena by two-and-a-half players: Despot, Tribune and the non-deterministic People. Despot wants to make the set of possible People's behaviors as small as possible, while Tribune wants to make it as large as possible.An MMG is played by two players that alternately write matrices from some predefined finite sets. One wants to maximize the growth rate of the product, and the other to minimize it. We show that in general MMGs are undecidable in quite a strong sense.On the positive side, EGs correspond to a subclass of MMGs, and we prove that such MMGs and EGs are determined, and that the optimal strategies are simple. The complexity of solving such games is in NP\&coNP.

cs.GT↗
arXiv2014

Optimal Strategy Synthesis for Request-Response Games

We show the existence and effective computability of optimal winning strategies for request-response games in case the quality of a play is measured by the limit superior of the mean accumulated waiting times between requests and their responses.

cs.FL↗
arXiv2012

The surprizing complexity of generalized reachability games

Games on graphs provide a natural and powerful model for reactive systems. In this paper, we consider generalized reachability objectives, defined as conjunctions of reachability objectives. We first prove that deciding the winner in such games is $\PSPACE$-complete, although it is fixed-parameter tractable with the number of reachability objectives as parameter. Moreover, we consider the memory requirements for both players and give matching upper and lower bounds on the size of winning strategies. In order to allow more efficient algorithms, we consider subclasses of generalized reachability games. We show that bounding the size of the reachability sets gives two natural subclasses where deciding the winner can be done efficiently.

cs.CC↗
arXiv2010

How do we remember the past in randomised strategies?

Graph games of infinite length are a natural model for open reactive processes: one player represents the controller, trying to ensure a given specification, and the other represents a hostile environment. The evolution of the system depends on the decisions of both players, supplemented by chance. In this work, we focus on the notion of randomised strategy. More specifically, we show that three natural definitions may lead to very different results: in the most general cases, an almost-surely winning situation may become almost-surely losing if the player is only allowed to use a weaker notion of strategy. In more reasonable settings, translations exist, but they require infinite memory, even in simple cases. Finally, some traditional problems becomes undecidable for the strongest type of strategies.

cs.GT↗
arXiv2009

Solving Simple Stochastic Games with Few Random Vertices

Simple stochastic games are two-player zero-sum stochastic games with turn-based moves, perfect information, and reachability winning conditions. We present two new algorithms computing the values of simple stochastic games. Both of them rely on the existence of optimal permutation strategies, a class of positional strategies derived from permutations of the random vertices. The "permutation-enumeration" algorithm performs an exhaustive search among these strategies, while the "permutation-improvement" algorithm is based on successive improvements, à la Hoffman-Karp. Our algorithms improve previously known algorithms in several aspects. First they run in polynomial time when the number of random vertices is fixed, so the problem of solving simple stochastic games is fixed-parameter tractable when the parameter is the number of random vertices. Furthermore, our algorithms do not require the input game to be transformed into a stopping game. Finally, the permutation-enumeration algorithm does not use linear programming, while the permutation-improvement algorithm may run in polynomial time.

cs.GT↗
arXiv2009

Random Fruits on the Zielonka Tree

Stochastic games are a natural model for the synthesis of controllers confronted to adversarial and/or random actions. In particular, $ω$-regular games of infinite length can represent reactive systems which are not expected to reach a correct state, but rather to handle a continuous stream of events. One critical resource in such applications is the memory used by the controller. In this paper, we study the amount of memory that can be saved through the use of randomisation in strategies, and present matching upper and lower bounds for stochastic Muller games.

cs.GT↗
arXiv2009

Self-stabilizing K-out-of-L exclusion on tree network

In this paper, we address the problem of K-out-of-L exclusion, a generalization of the mutual exclusion problem, in which there are $\ell$ units of a shared resource, and any process can request up to $\mathtt k$ units ($1\leq\mathtt k\leq\ell$). We propose the first deterministic self-stabilizing distributed K-out-of-L exclusion protocol in message-passing systems for asynchronous oriented tree networks which assumes bounded local memory for each process.

cs.NI↗