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Found 15 papers, 0 papers with code
Towards Efficient Risk-Sensitive Policy Gradient: An Iteration Complexity Analysis
In this study, we conduct a thorough iteration complexity analysis for the risk-sensitive policy gradient method, focusing on the REINFORCE algorithm and employing the exponential utility function.
Safe Collective Control under Noisy Inputs and Competing Constraints via Non-Smooth Barrier Functions
We consider the problem of safely coordinating ensembles of identical autonomous agents to conduct complex missions with conflicting safety requirements and under noisy control inputs.
Risk-Sensitive Inhibitory Control for Safe Reinforcement Learning
We propose a method for learning these value functions using common techniques from reinforcement learning and derive sufficient conditions for its success.
Consensus-Based Leader-Follower Formation Tracking for Control-Affine Nonlinear Multiagent Systems
To this end, we present consensus-based control laws for multiagent formation tracking in finite-dimensional state space, with the agents represented by a more general class of dynamics: control-affine nonlinear systems.
PASA: A Priori Adaptive Splitting Algorithm for the Split Delivery Vehicle Routing Problem
While the proposed a priori splitting rule in Chen et al. (2017) is fixed for all customers regardless of their demand and location, we suggest an adaptive splitting rule that takes into account the distance of the customers to the depot and their demand values.
Learning Agent Interactions from Density Evolution in 3D Regions With Obstacles
In this work, we study the inverse problem of identifying complex flocking dynamics in a domain cluttered with obstacles.
Mobile Network Slicing under Demand Uncertainty: A Stochastic Programming Approach
At each microscale instance, utilizing the exact slice demand profiles, a linear program is solved to jointly minimize the unsupported traffic and the resource cost at the RAN.
Capacitated Beam Placement for Multi-beam Non-Geostationary Satellite Systems
Non-geostationary (NGSO) satellite communications systems have attracted a lot of attention both from industry and academia, over the past several years.
Sensor Scheduling for Linear Systems: A Covariance Tracking Approach
We propose a convex relaxation to the sensor design problem and a reference covariance trajectory is obtained from solving the relaxed sensor design problem.
On the Importance of Trust in Next-Generation Networked CPS Systems: An AI Perspective
In the first example, we show how utilizing the trust evidence can improve the performance and the security of Federated Learning.
Value of information in networked control systems subject to delay
In this paper, we study the trade-off between the transmission cost and the control performance of the multi-loop networked control system subject to network-induced delay.
Joint Satellite Gateway Deployment & Controller Placement in Software-Defined 5G-Satellite Integrated Networks
Several challenging optimization problems arise while considering the deployment of the space-air-ground integrated networks (SAGINs), among which the optimal satellite gateway deployment problem is of significant importance.
Interpretable machine learning models: a physics-based view
We describe how we can build models out of the p-H constructs and how we can train them.
Fast Task-Specific Target Detection via Graph Based Constraints Representation and Checking
In this work, we present a fast target detection framework for real-world robotics applications.
Co-active Learning to Adapt Humanoid Movement for Manipulation
It is designed to adapt the original imitation trajectories, which are learned from demonstrations, to novel situations with various constraints.
