7 citations · 7 across the 3 of their papers we have counts for
4 papers
The price of decentralization in managing engineering systems through multi-agent reinforcement learning
Prateek Bhustali, Pablo G. Morato, Konstantinos G. Papakonstantinou +1
Inspection and maintenance (I&M) planning involves sequential decision making under uncertainties and incomplete information, and can be modeled as a partially observable Markov de…
Deep Belief Markov Models for POMDP Inference
Giacomo Arcieri, Konstantinos G. Papakonstantinou, Daniel Straub +1
This work introduces a novel deep learning-based architecture, termed the Deep Belief Markov Model (DBMM), which provides efficient, model-formulation agnostic inference in Partial…
Monitoring-Supported Value Generation for Managing Structures and Infrastructure Systems
Antonios Kamariotis, Eleni Chatzi, Daniel Straub +9
To maximize its value, the design, development and implementation of Structural Health Monitoring (SHM) should focus on its role in facilitating decision support. In this position…
Multi-agent deep reinforcement learning with centralized training and decentralized execution for transportation infrastructure management
M. Saifullah, K. G. Papakonstantinou, A. Bhattacharya +2
Life-cycle management of large-scale transportation systems requires determining a sequence of inspection and maintenance decisions to minimize long-term risks and costs while deal…