Tutorial LSI Design Contest Okinawa 🔗http://www.lsi-contest.com/2021/shiyou_3-1e.html Reinforcemet Learning 🔗 One of the fields of machine learning. Through trial and error, the agent (the body that performs an action) learns the behavior to be given the maximum reward. Sequence of reinforcement learning 🔗In reinforcement learning, learning is carried out by utilizing four elements of “Environment”, “Agent”, “Action”, and “Rewards”. Environment: Environments with agents Agent: Acting entities Action: The agent’s behavior Rewards: A reward for an action The sequence of reinforcement learning is shown in Fig.

Paper 1 🔗An Efficient Hardware Implementation of Reinforcement Learning: The Q-Learning Algorithm, IEEE Access https://ieeexplore.ieee.org/document/8937555 S. Spanò et al., “An Efficient Hardware Implementation of Reinforcement Learning: The Q-Learning Algorithm,” in IEEE Access, vol. 7, pp. 186340-186351, 2019, doi: 10.1109/ACCESS.2019.2961174. Abstract 🔗In this paper we propose an efficient hardware architecture that implements the Q-Learning algorithm, suitable for real-time applications. Its main features are low-power, high throughput and limited hardware resources. We also propose a technique based on approximated multipliers to reduce the hardware complexity of the algorithm.