59 citations · 364 across the 71 of their papers we have counts for
6 papers · 1 filter
Risk-Sensitive Reinforcement Learning with Exponential Criteria
Erfaun Noorani, Christos Mavridis, John Baras
While reinforcement learning has shown experimental success in a number of applications, it is known to be sensitive to noise and perturbations in the parameters of the system, lea…
Multi-Resolution Online Deterministic Annealing: A Hierarchical and Progressive Learning Architecture
Christos Mavridis, John Baras
Hierarchical learning algorithms that gradually approximate a solution to a data-driven optimization problem are essential to decision-making systems, especially under limitations…
Annealing Optimization for Progressive Learning with Stochastic Approximation
Christos Mavridis, John Baras
In this work, we introduce a learning model designed to meet the needs of applications in which computational resources are limited, and robustness and interpretability are priorit…
GAMEOPT: Optimal Real-time Multi-Agent Planning and Control for Dynamic Intersections
Nilesh Suriyarachchi, Rohan Chandra, John S. Baras +1
We propose GameOpt: a novel hybrid approach to cooperative intersection control for dynamic, multi-lane, unsignalized intersections. Safely navigating these complex and accident pr…
Multi-user Beam Alignment in Presence of Multi-path
Nariman Torkzaban, Mohammad A., Khojastepour +1
To overcome the high path-loss and the intense shadowing in millimeter-wave (mmWave) communications, effective beamforming schemes are required which incorporate narrow beams with…
Codebook Design for Composite Beamforming in Next-generation mmWave Systems
Nariman Torkzaban, Mohamamd A., Khojastepour +1
In pursuance of the unused spectrum in higher frequencies, millimeter wave (mmWave) bands have a pivotal role. However, the high path-loss and poor scattering associated with mmWav…