As the electricity market is progressively liberalized, virtual bidding has emerged as a novel participation mechanism attracting increasing attention. This paper integrates evolutionary game theory ...
This course introduces deterministic and stochastic dynamic optimization and reinforcement learning. The aims are (i) to motivate the use of dynamic optimization techniques (including reinforcement ...
Multi-Objective Reinforcement Learning (MORL) is an emerging field that extends the conventional reinforcement learning paradigm by enabling agents to optimise multiple conflicting objectives ...
Machines that learn like babies: Reinforcement learning expert David Silver speaking at the Heidelberg Laureate Forum on 15 September, 2025. (Courtesy: Bernhard Kreutzer/HLF) Today’s artificial ...
Progress in self-driving cars and other forms of automation will slow dramatically unless machines can hone skills through experience. Inside a simple computer simulation, a group of self-driving ...
Reinforcement Learning (RL) has rapidly emerged as a powerful approach for enabling robots to acquire adaptive, data-driven behaviors in real-world ...
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