[HTML][HTML] Deep reinforcement learning for inventory control: A roadmap
Deep reinforcement learning (DRL) has shown great potential for sequential decision-
making, including early developments in inventory control. Yet, the abundance of choices …
making, including early developments in inventory control. Yet, the abundance of choices …
A state‐of‐the‐art review of optimal reservoir control for managing conflicting demands in a changing world
The state of the art for optimal water reservoir operations is rapidly evolving, driven by
emerging societal challenges. Changing values for balancing environmental resources …
emerging societal challenges. Changing values for balancing environmental resources …
Legged locomotion in challenging terrains using egocentric vision
Animals are capable of precise and agile locomotion using vision. Replicating this ability
has been a long-standing goal in robotics. The traditional approach has been to decompose …
has been a long-standing goal in robotics. The traditional approach has been to decompose …
Provable benefits of actor-critic methods for offline reinforcement learning
Actor-critic methods are widely used in offline reinforcement learningpractice, but are not so
well-understood theoretically. We propose a newoffline actor-critic algorithm that naturally …
well-understood theoretically. We propose a newoffline actor-critic algorithm that naturally …
[LIVRE][B] Mathematical control theory for stochastic partial differential equations
Q Lü, X Zhang - 2021 - Springer
It is well-known that Control Theory was founded by N. Wiener in 1948 ([349]). After that, this
theory was greatly extended to various complicated setting and widely used in sciences and …
theory was greatly extended to various complicated setting and widely used in sciences and …
[PDF][PDF] Foundations of machine learning
M Mohri - 2018 - dlib.hust.edu.vn
A new edition of a graduate-level machine learning textbook that focuses on the analysis
and theory of algorithms. This book is a general introduction to machine learning that can …
and theory of algorithms. This book is a general introduction to machine learning that can …
Neuromodulated spike-timing-dependent plasticity, and theory of three-factor learning rules
Classical Hebbian learning puts the emphasis on joint pre-and postsynaptic activity, but
neglects the potential role of neuromodulators. Since neuromodulators convey information …
neglects the potential role of neuromodulators. Since neuromodulators convey information …
Model-based reinforcement learning with a generative model is minimax optimal
This work considers the sample and computational complexity of obtaining an $\epsilon $-
optimal policy in a discounted Markov Decision Process (MDP), given only access to a …
optimal policy in a discounted Markov Decision Process (MDP), given only access to a …
[LIVRE][B] Scheduling
ML Pinedo - 2012 - Springer
Michael L. Pinedo Theory, Algorithms, and Systems Sixth Edition Page 1 Scheduling Michael L.
Pinedo Theory, Algorithms, and Systems Sixth Edition Page 2 Scheduling Page 3 Michael L …
Pinedo Theory, Algorithms, and Systems Sixth Edition Page 2 Scheduling Page 3 Michael L …
[LIVRE][B] Planning algorithms
SM LaValle - 2006 - books.google.com
Planning algorithms are impacting technical disciplines and industries around the world,
including robotics, computer-aided design, manufacturing, computer graphics, aerospace …
including robotics, computer-aided design, manufacturing, computer graphics, aerospace …