Introduces reinforcement learning, covering its definitions, applications, and theoretical foundations, while outlining the course structure and objectives.
Explores energy conservation in Hamiltonian systems, numerical integration, time step choices, and constraint algorithms in molecular dynamics simulations.
Explores the financial applications of blockchains, covering the definition, history, Ethereum, decentralized finance, smart contracts, tokens, assessment methods, challenges of double spending, digital signatures, and cryptographic hash functions.
Explores safe learning in robotics, covering the state of the art, open challenges, and vision in the field, emphasizing the importance of interdisciplinary collaboration.
