Vojtěch Kůr
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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: Steady-State Strategy Synthesis for Swarms of Autonomous Agents
Steady-State Strategy Synthesis for Swarms of Autonomous Agents Open
Steady-state synthesis aims to construct a policy for a given MDP $D$ such that the long-run average frequencies of visits to the vertices of $D$ satisfy given numerical constraints. This problem is solvable in polynomial time, and memoryl…
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…
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…