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cs.LG2024

Accelerating Proximal Policy Optimization Learning Using Task Prediction for Solving Environments with Delayed Rewards

Ahmad Ahmad, Mehdi Kermanshah, Kevin Leahy +6

In this paper, we tackle the challenging problem of delayed rewards in reinforcement learning (RL). While Proximal Policy Optimization (PPO) has emerged as a leading Policy Gradien…

cs.RO2024

Model Predictive Control for Magnetically-Actuated Cellbots

Mehdi Kermanshah, Logan E. Beaver, Max Sokolich +5

This paper presents a control framework for magnetically actuated cellbots, which combines Model Predictive Control (MPC) with Gaussian Processes (GPs) as a disturbance estimator f…

eess.SY2024

Distance-coupling as an Approach to Position and Formation Control

Michael Napoli, Roberto Tron

In this letter, we study the case of autonomous agents which are required to move to some new position based solely on the distance measured from predetermined reference points, or…

stat.ML2024

Multi-class Temporal Logic Neural Networks

Danyang Li, Roberto Tron

Time-series data can represent the behaviors of autonomous systems, such as drones and self-driving cars. The task of binary and multi-class classification for time-series data has…

math.DS2024

Navigating the Noise: A CBF Approach for Nonlinear Control with Integral Constraints

Idris Seidu, Roberto Tron

Many physical phenomena involving mobile agents involve time-varying scalar fields, e.g., quadrotors that emit noise. As a consequence, agents can influence and can be influenced b…

cs.LO2024

TLINet: Differentiable Neural Network Temporal Logic Inference

Danyang Li, Mingyu Cai, Cristian-Ioan Vasile +1

There has been a growing interest in extracting formal descriptions of the system behaviors from data. Signal Temporal Logic (STL) is an expressive formal language used to describe…