Search Results for author: Karl H. Johansson

Found 30 papers, 3 papers with code

Distributed Computation of Exact Average Degree and Network Size in Finite Number of Steps under Quantized Communication

no code implementations29 Nov 2022 Apostolos I. Rikos, Themistoklis Charalambous, Christoforos N. Hadjicostis, Karl H. Johansson

We present two distributed algorithms which rely on quantized operation (i. e., nodes process and transmit quantized messages), and are able to calculate the exact solutions in a finite number of steps.


Finite-Time Distributed Optimization with Quantized Gradient Descent

no code implementations20 Nov 2022 Apostolos I. Rikos, Wei Jiang, Themistoklis Charalambous, Karl H. Johansson

In this paper, we consider the unconstrained distributed optimization problem, in which the exchange of information in the network is captured by a directed graph topology, and thus nodes can send information to their out-neighbors only.

Distributed Optimization

Safe Reinforcement Learning using Data-Driven Predictive Control

no code implementations20 Nov 2022 Mahmoud Selim, Amr Alanwar, M. Watheq El-Kharashi, Hazem M. Abbas, Karl H. Johansson

If there is an intersection between the reachable set of the robot using the proposed action, we call the data-driven predictive controller to find the closest safe action to the proposed unsafe action.

Continuous Control Decision Making +2

Secure State Estimation against Sparse Attacks on a Time-varying Set of Sensors

no code implementations10 Nov 2022 Zishuo Li, Muhammad Umar B. Niazi, Changxin Liu, Yilin Mo, Karl H. Johansson

At each time step, the local estimates of sensors are fused by solving an optimization problem to obtain a secure estimation, which is then followed by a local detection-and-resetting process of the decentralized observers.

Logical Zonotope: A Set Representation for Binary Vectors

1 code implementation16 Oct 2022 Amr Alanwar, Frank J. Jiang, Samy Amin, Karl H. Johansson

In this paper, we propose a new set representation for binary vectors called logical zonotopes.

A Zeroth-Order Momentum Method for Risk-Averse Online Convex Games

no code implementations6 Sep 2022 Zifan Wang, Yi Shen, Zachary I. Bell, Scott Nivison, Michael M. Zavlanos, Karl H. Johansson

Specifically, the agents use the conditional value at risk (CVaR) as a risk measure and rely on bandit feedback in the form of the cost values of the selected actions at every episode to estimate their CVaR values and update their actions.

A Sample-Based Algorithm for Approximately Testing $r$-Robustness of a Digraph

no code implementations25 Jul 2022 Yuhao Yi, YuAn Wang, Xingkang He, Stacy Patterson, Karl H. Johansson

In this paper, we propose a sample-based algorithm to approximately test $r$-robustness of a digraph with $n$ vertices and $m$ edges.

Distributed Finite Time k-means Clustering with Quantized Communucation and Transmission Stopping

no code implementations17 Jul 2022 Apostolos I. Rikos, Gabriele Oliva, Christoforos N. Hadjicostis, Karl H. Johansson

The goal of $k$-means is to partition the network's agents in mutually exclusive sets (groups) such that agents in the same set have (and possibly share) similar information and are able to calculate a representative value for their group. During the operation of our distributed algorithm, each node (i) transmits quantized values in an event-driven fashion, and (ii) exhibits distributed stopping capabilities.

Finite Time Privacy Preserving Quantized Average Consensus with Transmission Stopping

no code implementations17 Jul 2022 Apostolos I. Rikos, Christoforos N. Hadjicostis, Karl H. Johansson

Furthermore, we present topological conditions under which the proposed algorithm allows nodes to preserve their privacy.

Privacy Preserving

Safe Reinforcement Learning Using Black-Box Reachability Analysis

1 code implementation15 Apr 2022 Mahmoud Selim, Amr Alanwar, Shreyas Kousik, Grace Gao, Marco Pavone, Karl H. Johansson

Reinforcement learning (RL) is capable of sophisticated motion planning and control for robots in uncertain environments.

Motion Planning reinforcement-learning +1

Truck Platoon Formation at Hubs: An Optimal Release Time Rule

no code implementations18 Feb 2022 Alexander Johansson, Valerio Turri, Ehsan Nekouei, Karl H. Johansson, Jonas Mårtensson

The vehicles wait at the hub, and a platoon coordinator, at each time-step, decides whether to release the vehicles from the hub in the form of a platoon or wait for more vehicles to arrive.

Data-driven Set-based Estimation of Polynomial Systems with Application to SIR Epidemics

no code implementations8 Nov 2021 Amr Alanwar, Muhammad Umar B. Niazi, Karl H. Johansson

The offline phase utilizes past input-output data to estimate a set of possible coefficients of the polynomial system.

Finite Time Exact Quantized Average Consensus with Limited Resources and Transmission Stopping for Energy-Aware Networks

no code implementations1 Oct 2021 Apostolos I. Rikos, Christoforos N. Hadjicostis, Karl H. Johansson

Motivated by these novel requirements, in this paper, we present and analyze a novel distributed average consensus algorithm, which (i) operates exclusively on quantized values (in order to guarantee efficient communication and data storage), and (ii) relies on event-driven updates (in order to reduce energy consumption, communication bandwidth, network congestion, and/or processor usage).

Autonomous Vehicles

Distributed Optimal Allocation with Quantized Communication and Privacy-Preserving Guarantees

no code implementations29 Sep 2021 Jakob Nylöf, Apostolos I. Rikos, Sebin Gracy, Karl H. Johansson

It is shown that the proposed privacy-preserving resource allocation algorithm performs well with an appropriate convergence rate under privacy guarantees.

Privacy Preserving

Computing Complexity-aware Plans Using Kolmogorov Complexity

no code implementations21 Sep 2021 Elis Stefansson, Karl H. Johansson

We present two algorithms obtaining low-complexity policies, where the first algorithm obtains a low-complexity optimal policy, and the second algorithm finds a policy maximising performance while maintaining local (stage-wise) complexity constraints.

Multi-Layer SIS Model with an Infrastructure Network

no code implementations20 Sep 2021 Philip E. Pare, Axel Janson, Sebin Gracy, Ji Liu, Henrik Sandberg, Karl H. Johansson

We develop a layered networked spread model for a susceptible-infected-susceptible (SIS) pathogen-borne disease spreading over a human contact network and an infrastructure network, and refer to it as a layered networked susceptible-infected-water-susceptible (SIWS) model.

Regret and Cumulative Constraint Violation Analysis for Online Convex Optimization with Long Term Constraints

no code implementations9 Jun 2021 Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, Karl H. Johansson

A novel algorithm is first proposed and it achieves an $\mathcal{O}(T^{\max\{c, 1-c\}})$ bound for static regret and an $\mathcal{O}(T^{(1-c)/2})$ bound for cumulative constraint violation, where $c\in(0, 1)$ is a user-defined trade-off parameter, and thus has improved performance compared with existing results.

A Model Randomization Approach to Statistical Parameter Privacy

no code implementations22 May 2021 Ehsan Nekouei, Henrik Sandberg, Mikael Skoglund, Karl H. Johansson

To ensure parameter privacy, we propose a filter design framework which consists of two components: a randomizer and a nonlinear transformation.

Geometrical Characterization of Sensor Placement for Cone-Invariant and Multi-Agent Systems against Undetectable Zero-Dynamics Attacks

no code implementations10 May 2021 Jianqi Chen, Jieqiang Wei, Wei Chen, Henrik Sandberg, Karl H. Johansson, Jie Chen

Undetectable attacks are an important class of malicious attacks threatening the security of cyber-physical systems, which can modify a system's state but leave the system output measurements unaffected, and hence cannot be detected from the output.

Regret and Cumulative Constraint Violation Analysis for Distributed Online Constrained Convex Optimization

no code implementations1 May 2021 Xinlei Yi, Xiuxian Li, Tao Yang, Lihua Xie, Tianyou Chai, Karl H. Johansson

This is a sequential decision making problem with two sequences of arbitrarily varying convex loss and constraint functions.

Decision Making

Stochastic Stability of Discrete-time Phase-coupled Oscillators over Uncertain and Random Networks

no code implementations12 Apr 2021 Matin Jafarian, Mohammad H. Mamduhi, Karl H. Johansson

We assume constant exogenous frequencies and derive sufficient conditions for achieving both stochastic phase-cohesive and phase-locked solutions, i. e., the stochastic phase-cohesiveness with respect to the origin.

Stability Conditions for Remote State Estimation of Multiple Systems over Multiple Markov Fading Channels

no code implementations9 Apr 2021 Wanchun Liu, Daniel E. Quevedo, Karl H. Johansson, Branka Vucetic, Yonghui Li

We investigate the stability conditions for remote state estimation of multiple linear time-invariant (LTI) systems over multiple wireless time-varying communication channels.

Event-Triggered Distributed Estimation With Decaying Communication Rate

no code implementations10 Mar 2021 Xingkang He, Yu Xing, Junfeng Wu, Karl H. Johansson

We show that given the step size, adjusting the decay speed of the triggering threshold can lead to a tradeoff between the convergence rate of the estimation error and the decay speed of the communication rate.

Community Structure Recovery and Interaction Probability Estimation for Gossip Opinion Dynamics

no code implementations19 Feb 2021 Yu Xing, Xingkang He, Haitao Fang, Karl H. Johansson

It is assumed that each agent is assigned with one of two community labels, and the agents interact with probabilities depending on their labels.

Community Detection

A Primal-Dual SGD Algorithm for Distributed Nonconvex Optimization

no code implementations4 Jun 2020 Xinlei Yi, Shengjun Zhang, Tao Yang, Tianyou Chai, Karl H. Johansson

The distributed nonconvex optimization problem of minimizing a global cost function formed by a sum of $n$ local cost functions by using local information exchange is considered.

Optimization and Control

How to Secure Distributed Filters Under Sensor Attacks

no code implementations11 Apr 2020 Xingkang He, Xiaoqiang Ren, Henrik Sandberg, Karl H. Johansson

The resilience of the secured filter with detection is verified by an explicit relationship between the upper bound of the estimation error and the number of detected attacked sensors.

Distributed Online Convex Optimization with Time-Varying Coupled Inequality Constraints

no code implementations6 Mar 2019 Xinlei Yi, Xiuxian Li, Lihua Xie, Karl H. Johansson

Assuming Slater's condition, we show that the algorithm achieves smaller bounds on the constraint violation.

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