no code implementations • 2 May 2024 • Mahdieh Zaker, Henk A. P. Blom, Sadegh Soudjani, Abolfazl Lavaei
In our proposed setting, the situation awareness is considered for one of the ego vehicles by aggregating a range of diverse information gathered from other vehicles into a vector.
1 code implementation • 23 Apr 2024 • Ben Wooding, Viacheslav Horbanov, Abolfazl Lavaei
We develop an open-source software tool, called PRoTECT, for the parallelized construction of safety barrier certificates (BCs) for nonlinear polynomial systems.
1 code implementation • 7 Jan 2024 • Ben Wooding, Abolfazl Lavaei
This paper is concerned with developing a software tool, called IMPaCT, for the parallelized verification and controller synthesis of large-scale stochastic systems using interval Markov chains (IMCs) and interval Markov decision processes (IMDPs), respectively.
no code implementations • 14 Sep 2023 • Abolfazl Lavaei
We construct a symbolic abstraction from data for each room as an appropriate substitute of original system and compositionally synthesize controllers regulating the temperature of each room within a safe zone with some guaranteed probabilistic confidence.
no code implementations • 14 Sep 2023 • Abolfazl Lavaei
This work proposes a compositional data-driven technique for the construction of finite Markov decision processes (MDPs) for large-scale stochastic networks with unknown mathematical models.
no code implementations • 11 Sep 2023 • Omid Akbarzadeh, Sadegh Soudjani, Abolfazl Lavaei
This work is concerned with a formal approach for safety controller synthesis of stochastic control systems with both process and measurement noises while considering wireless communication networks between sensors, controllers, and actuators.
no code implementations • 6 Aug 2022 • Abolfazl Lavaei, Mateo Perez, Milad Kazemi, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi, Majid Zamani
A key contribution is to leverage the convergence results for adversarial RL (minimax Q-learning) on finite stochastic arenas to provide control strategies maximizing the probability of satisfaction over the network of continuous-space systems.
no code implementations • 6 Aug 2022 • Abolfazl Lavaei, Sadegh Soudjani, Emilio Frazzoli
In our proposed scheme, we first provide an augmented framework to characterize each stochastic hybrid system containing continuous evolutions and instantaneous jumps with a unified system covering both scenarios.
no code implementations • 6 Aug 2022 • Abolfazl Lavaei, Emilio Frazzoli
We apply our results to a room temperature network of 200 rooms with Markovian switching signals while accepting multiple storage certificates.
no code implementations • 29 Jun 2022 • Abolfazl Lavaei, Sadegh Soudjani, Emilio Frazzoli, Majid Zamani
We then propose a scenario convex program (SCP) associated to the original RCP by collecting a finite number of data from trajectories of the system.
no code implementations • 19 Jun 2022 • Abolfazl Lavaei, Emilio Frazzoli
In this work, we propose a data-driven approach for the construction of finite abstractions (a. k. a., symbolic models) for discrete-time deterministic control systems with unknown dynamics.
no code implementations • 23 Dec 2021 • Ali Salamati, Abolfazl Lavaei, Sadegh Soudjani, Majid Zamani
In this paper, we propose a data-driven approach to formally verify the safety of (potentially) unknown discrete-time continuous-space stochastic systems.
no code implementations • 14 Dec 2021 • Abolfazl Lavaei, Luigi Di Lillo, Andrea Censi, Emilio Frazzoli
The proposed approach is based on the construction of sub-barrier certificates for each stochastic agent via a set of data collected from its trajectories while providing an a-priori guaranteed confidence on the data-driven estimation.
no code implementations • 19 Nov 2021 • Ali Salamati, Abolfazl Lavaei, Sadegh Soudjani, Majid Zamani
In this work, we study verification and synthesis problems for safety specifications over unknown discrete-time stochastic systems.
no code implementations • 23 Apr 2021 • Bingzhuo Zhong, Abolfazl Lavaei, Majid Zamani, Marco Caccamo
In this work, we propose an abstraction and refinement methodology for the controller synthesis of discrete-time stochastic systems to enforce complex logical properties expressed by deterministic finite automata (a. k. a.
no code implementations • 3 Mar 2021 • Mahathi Anand, Abolfazl Lavaei, Majid Zamani
This paper is concerned with a compositional scheme for the construction of control barrier certificates for interconnected discrete-time stochastic systems.
no code implementations • 10 Feb 2021 • Bingzhuo Zhong, Abolfazl Lavaei, Hongpeng Cao, Majid Zamani, Marco Caccamo
To cope with this difficulty, we propose in this work a Safe-visor architecture for sandboxing unverified controllers in CPSs operating in noisy environments (a. k. a.
no code implementations • 18 Jan 2021 • Mahathi Anand, Abolfazl Lavaei, Majid Zamani
This paper is concerned with a compositional approach for the construction of control barrier certificates for large-scale interconnected stochastic systems while synthesizing hybrid controllers against high-level logic properties.
no code implementations • 2 Mar 2020 • Abolfazl Lavaei, Fabio Somenzi, Sadegh Soudjani, Ashutosh Trivedi, Majid Zamani
A key contribution of the paper is to leverage the classical convergence results for reinforcement learning on finite MDPs and provide control strategies maximizing the probability of satisfaction over unknown, continuous-space MDPs while providing probabilistic closeness guarantees.