Artificial intelligence applications in supply chain management
M Pournader, H Ghaderi, A Hassanzadegan… - International Journal of …, 2021 - Elsevier
This paper presents a systematic review of studies related to artificial intelligence (AI)
applications in supply chain management (SCM). Our systematic search of the related …
applications in supply chain management (SCM). Our systematic search of the related …
An overview of multi-agent reinforcement learning from game theoretical perspective
Y Yang, J Wang - arXiv preprint arXiv:2011.00583, 2020 - arxiv.org
Following the remarkable success of the AlphaGO series, 2019 was a booming year that
witnessed significant advances in multi-agent reinforcement learning (MARL) techniques …
witnessed significant advances in multi-agent reinforcement learning (MARL) techniques …
Minimum cost flows, MDPs, and ℓ1-regression in nearly linear time for dense instances
In this paper we provide new randomized algorithms with improved runtimes for solving
linear programs with two-sided constraints. In the special case of the minimum cost flow …
linear programs with two-sided constraints. In the special case of the minimum cost flow …
Deep learning in neural networks: An overview
J Schmidhuber - Neural networks, 2015 - Elsevier
In recent years, deep artificial neural networks (including recurrent ones) have won
numerous contests in pattern recognition and machine learning. This historical survey …
numerous contests in pattern recognition and machine learning. This historical survey …
Reinforcement learning approaches in social robotics
This article surveys reinforcement learning approaches in social robotics. Reinforcement
learning is a framework for decision-making problems in which an agent interacts through …
learning is a framework for decision-making problems in which an agent interacts through …
Reinforcement learning based resource management for fog computing environment: Literature review, challenges, and open issues
In the IoT-based systems, the fog computing allows the fog nodes to offload and process
tasks requested from IoT-enabled devices in a distributed manner instead of the centralized …
tasks requested from IoT-enabled devices in a distributed manner instead of the centralized …
Average age of information with hybrid ARQ under a resource constraint
Scheduling the transmission of status updates over an error-prone communication channel
is studied in order to minimize the long-term average age of information at the destination …
is studied in order to minimize the long-term average age of information at the destination …
Game theoretic modeling of driver and vehicle interactions for verification and validation of autonomous vehicle control systems
Autonomous driving has been the subject of incre-ased interest in recent years both in
industry and in academia. Serious efforts are being pursued to address legal, technical, and …
industry and in academia. Serious efforts are being pursued to address legal, technical, and …
On the convergence of projective-simulation–based reinforcement learning in Markov decision processes
WL Boyajian, J Clausen, LM Trenkwalder… - Quantum machine …, 2020 - Springer
In recent years, the interest in leveraging quantum effects for enhancing machine learning
tasks has significantly increased. Many algorithms speeding up supervised and …
tasks has significantly increased. Many algorithms speeding up supervised and …
Learning-based control: A tutorial and some recent results
This monograph presents a new framework for learning-based control synthesis of
continuous-time dynamical systems with unknown dynamics. The new design paradigm …
continuous-time dynamical systems with unknown dynamics. The new design paradigm …