Humans and other animals are constantly required to make decisions under uncertain conditions or while in rapidly changing environments. Past psychology and biology studies showed that some ...

Microsoft Research conducts fundamental science and technology research across a spectrum of research areas. With labs around the globe we pursue breakthroughs across the computing and AI stack to ...

Combinatorial optimization underpins applications in artificial intelligence, logistics, and network design, yet classical techniques such as greedy search and dynamic programming struggle to balance ...

This paper presents an optimized strategy for multiple integrations of photovoltaic distributed generation (PV-DG) within radial distribution power systems. The proposed methodology focuses on ...

Large-scale distributed renewable energy in the distribution network can result in reliability issues such as exceeding voltage limits and overloading power lines. Additionally, the rapid growth of ...

Abstract: The consideration of reliability in controller design is able to avoid the potential actuator faults from inappropriate strategies. This work presents an optimal reliability-critical ...

Machine learning is the study of intelligent machines that can learn from data and anticipate future outcomes. One of the most important components of machine learning is dealing with uncertainty, ...

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Abstract: In this paper, we develop approximate dynamic programming methods for stochastic systems modeled as Markov Decision Processes, given both soft performance criteria and hard constraints in a ...