Abstract: Q-Learning, which is a well-known model-free reinforcement learning algorithm, a learning agent explores an environment to update a state-action function. In reinforcement learning, the ...

Abstract: This letter proposes a new scheme that uses Reward Function Learning for Q-learning-based Geographic routing (RFLQGeo) to improve the performance and efficiency of unmanned robotic networks ...

At the core of Industry 4.0, the smart factory integrates automation, mass customization, and self-organization into a highly ...

If you have any confusion about the code or want to report a bug, please open an issue instead of emailing me directly, and unfortunately I do not have exercise answers for the book.

Multi-Pass Deep Q-Networks (MP-DQN) fixes the over-paramaterisation problem of P-DQN by splitting the action-parameter inputs to the Q-network using several passes (in a parallel batch). Split Deep ...

A deep reinforcement learning framework optimizes silicon-based photonic crystal fiber modulators, achieving ultra-low ...

Quantori, a leading provider of digital transformation services and technology for the life sciences and healthcare industries, today announced that its MLConformerGenerator solution has been selected ...

A lot of companies suddenly seem to be hiring FDEs to oversee successful AI deployments. With that in mind, AWS exec Taimur Rashid talked about how his company approaches the role, what FDEs do, and ...

Antitrust laws presume a meeting of minds. Section 3(1) of the Competition Act, 2002 prohibits any agreement causing an appreciable adverse effect on competitio ...

Revenue in the city’s General Fund budget, which covers most day-to-day city expenses, including salaries, ...

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