Vojtěch Řehák
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View article: Memory Assignment for Finite-Memory Strategies in Adversarial Patrolling Games
Memory Assignment for Finite-Memory Strategies in Adversarial Patrolling Games Open
Adversarial Patrolling games form a subclass of Security games where a Defender moves between locations, guarding vulnerable targets. The main algorithmic problem is constructing a strategy for the Defender that minimizes the worst damage …
View article: Multiple Mean-Payoff Optimization Under Local Stability Constraints
Multiple Mean-Payoff Optimization Under Local Stability Constraints Open
The long-run average payoff per transition (mean payoff) is the main tool for specifying the performance and dependability properties of discrete systems. The problem of constructing a controller (strategy) simultaneously optimizing severa…
View article: Multiple Mean-Payoff Optimization under Local Stability Constraints
Multiple Mean-Payoff Optimization under Local Stability Constraints Open
The long-run average payoff per transition (mean payoff) is the main tool for specifying the performance and dependability properties of discrete systems. The problem of constructing a controller (strategy) simultaneously optimizing severa…
Who Let the Guards Out: Visual Support for Patrolling Games Open
Effective security patrol management is critical for ensuring safety in diverse environments such as art galleries, airports, and factories. The behavior of patrols in these situations can be modeled by patrolling games. They simulate the …
Decidable Race Condition and Open Coregions in HMSC Open
Message Sequence Charts (MSCs) is a visual formalism for the description of communication behaviour of distributed systems. An MSC specifies relations between communication events with partial orders. A situation when two visually ordered …
View article: Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes
Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes Open
Long-run average optimization problems for Markov decision processes (MDPs) require constructing policies with optimal steady-state behavior, i.e., optimal limit frequency of visits to the states. However, such policies may suffer from loc…
View article: Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes
Optimizing Local Satisfaction of Long-Run Average Objectives in Markov Decision Processes Open
Long-run average optimization problems for Markov decision processes (MDPs) require constructing policies with optimal steady-state behavior, i.e., optimal limit frequency of visits to the states. However, such policies may suffer from loc…
Mean Payoff Optimization for Systems of Periodic Service and Maintenance Open
Consider oriented graph nodes requiring periodic visits by a service agent. The agent moves among the nodes and receives a payoff for each completed service task, depending on the time elapsed since the previous visit to a node. We conside…
Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems Open
We consider the problem of synthesizing resilient and stochastically stable strategies for systems of cooperating agents striving to minimize the expected time between consecutive visits to selected locations in a known environment. A stra…
Synthesizing Resilient Strategies for Infinite-Horizon Objectives in Multi-Agent Systems Open
We consider the problem of synthesizing resilient and stochastically stable strategies for systems of cooperating agents striving to minimize the expected time between consecutive visits to selected locations in a known environment. A stra…
Mean Payoff Optimization for Systems of Periodic Service and Maintenance Open
Consider oriented graph nodes requiring periodic visits by a service agent. The agent moves among the nodes and receives a payoff for each completed service task, depending on the time elapsed since the previous visit to a node. We conside…
General Optimization Framework for Recurrent Reachability Objectives Open
We consider the mobile robot path planning problem for a class of recurrent reachability objectives. These objectives are parameterized by the expected time needed to visit one position from another, the expected square of this time, and a…
On-the-fly Adaptation of Patrolling Strategies in Changing Environments Open
We consider the problem of efficient patrolling strategy adaptation in a changing environment where the topology of Defender's moves and the importance of guarded targets change unpredictably. The Defender must instantly switch to a new st…
General Optimization Framework for Recurrent Reachability Objectives Open
We consider the mobile robot path planning problem for a class of recurrent reachability objectives. These objectives are parameterized by the expected time needed to visit one position from another, the expected square of this time, and a…
Minimizing Expected Intrusion Detection Time in Adversarial Patrolling Open
In adversarial patrolling games, a mobile Defender strives to discover intrusions at vulnerable targets initiated by an Attacker. The Attacker's utility is traditionally defined as the probability of completing an attack, possibly weighted…
Regstar: Efficient Strategy Synthesis for Adversarial Patrolling Games Open
We design a new efficient strategy synthesis method applicable to adversarial patrolling problems on graphs with arbitrary-length edges and possibly imperfect intrusion detection. The core ingredient is an efficient algorithm for computing…
Regstar: Efficient Strategy Synthesis for Adversarial Patrolling Games Open
We design a new efficient strategy synthesis method applicable to adversarial patrolling problems on graphs with arbitrary-length edges and possibly imperfect intrusion detection. The core ingredient is an efficient algorithm for computing…
Solving Patrolling Problems in the Internet Environment Open
We propose an algorithm for constructing efficient patrolling strategies in the Internet environment, where the protected targets are nodes connected to the network and the patrollers are software agents capable of detecting/preventing und…
Synthesizing Efficient Solutions for Patrolling Problems in the Internet Environment Open
We propose an algorithm for constructing efficient patrolling strategies in the Internet environment, where the protected targets are nodes connected to the network and the patrollers are software agents capable of detecting/preventing und…
Synthesizing Efficient Solutions for Patrolling Problems in the Internet Environment Open
We propose an algorithm for constructing efficient patrolling strategies in the Internet environment, where the protected targets are nodes connected to the network and the patrollers are software agents capable of detecting/preventing und…
Mean-Payoff Optimization in Continuous-Time Markov Chains with\n Parametric Alarms Open
Continuous-time Markov chains with alarms (ACTMCs) allow for alarm events\nthat can be non-exponentially distributed. Within parametric ACTMCs, the\nparameters of alarm-event distributions are not given explicitly and can be\nsubject of pa…
Efficient Timeout Synthesis in Fixed-Delay CTMC Using Policy Iteration Open
We consider the fixed-delay synthesis problem for continuous-time Markov chains extended with fixed-delay transitions (fdCTMC). The goal is to synthesize concrete values of the fixed-delays (timeouts) that minimize the expected total cost …
Extension of PRISM by Synthesis of Optimal Timeouts in Fixed-Delay CTMC Open
We present a practically appealing extension of the probabilistic model checker PRISM rendering it to handle fixed-delay continuous-time Markov chains (fdCTMCs) with rewards, the equivalent formalism to the deterministic and stochastic Pet…