Publications associées à From Nondeterministic Buchi and Streett Automata to Deterministic Parity Automata

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Rationally almost periodic sequences, polynomial multiple recurrence and symbolic dynamics

Florian Karl Richter

A set

R\subset \mathbb{N}

is called rational if it is well approximable by finite unions of arithmetic progressions, meaning that for every

\unicode[STIX]{x1D716}>0

there exists a set

B=\bigcup _{i=1}^{r}a_{i}\mathbb{N}+b_{i}

, where $a_{1},\ldots ,a_ ...

2019

From Nondeterministic Buchi and Streett Automata to Deterministic Parity Automata

Graph Chatbot

Chattez avec Graph Search

Lower Bounds for Unambiguous Automata via Communication Complexity

Rationally almost periodic sequences, polynomial multiple recurrence and symbolic dynamics

Control synthesis for stochastic systems given automata specifications defined by stochastic sets

Measuring and Synthesizing Systems in Probabilistic Environments

On the Dispersions of the Gel'fand-Pinsker Channel and Dirty Paper Coding

Formalization, Implementation, and Modeling of Institutional Controllers for Distributed Robotic Systems

For Coordination, State Component Transitions

Integration of BIP into Connectivity Factory: Implementation

Control design for specifications on stochastic hybrid systems

Symbolic execution of Reo circuits using constraint automata

Lower Bounds for Unambiguous Automata via Communication Complexity

Control synthesis for stochastic systems given automata specifications defined by stochastic sets

Symbolic execution of Reo circuits using constraint automata

On the Dispersions of the Gel'fand-Pinsker Channel and Dirty Paper Coding

Rationally almost periodic sequences, polynomial multiple recurrence and symbolic dynamics

For Coordination, State Component Transitions

Formalization, Implementation, and Modeling of Institutional Controllers for Distributed Robotic Systems

Integration of BIP into Connectivity Factory: Implementation

Control design for specifications on stochastic hybrid systems

Measuring and Synthesizing Systems in Probabilistic Environments