gentleshaid in #leofinance • 39 minutes ago@gentleshaid "Same issue. Invalid invite..."Same issue. Invalid invitegentleshaid in #leofinance • 1 hour ago@gentleshaid "This is what I got https://img.inleo.io/DQmb9C6T4..."This is what I gotai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 5/5: In closing, Ng expresses gratitude"Part 5/5: In closing, Ng expresses gratitude for the hard work the students have put into the course, and hopes they will use their newfound expertise to pursue impactful and…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 4/5: Looking to the future, Ng"Part 4/5: Looking to the future, Ng believes that reinforcement learning will have its biggest impact in robotics applications, beyond just game-playing. He cites examples like…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 3/5: Ng walks through the mathematical"Part 3/5: Ng walks through the mathematical formulation of a policy search algorithm called REINFORCE. He shows how it can be derived as a stochastic gradient ascent method to…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 2/5: Ng explains that the bottleneck"Part 2/5: Ng explains that the bottleneck in the development process often shifts between these three areas, requiring an iterative approach to improve the system. He…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 1/5: # Reinforcement Learning and the"Part 1/5: Reinforcement Learning and the Future of AI Wrapping Up Reinforcement Learning Andrew Ng begins by wrapping up the discussion on reinforcement learning, which has…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 3/3: - An interesting property is"Part 3/3: An interesting property is that the optimal policy does not depend on the noise covariance Σ_w, only the system matrices A and B. Overall, these generalizations…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 2/3: - This can model scenarios"Part 2/3: This can model scenarios with time-varying dynamics or costs, e.g. rush hour traffic, weather changes, or factory labor availability. The optimal value function…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 1/3: # Generalizations of Reinforcement Learning"Part 1/3: Generalizations of Reinforcement Learning and MDPs State-Action Rewards The reward function R can be a function mapping from states and actions to rewards…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 5/5: - Overall, model-based reinforcement learning"Part 5/5: Overall, model-based reinforcement learning using fitted value iteration provides a principled approach for tackling continuous state MDPs, allowing the value…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 4/5: - This iteratively improves the"Part 4/5: This iteratively improves the value function approximation by fitting a linear model to the sampled state-value pairs. The final policy is then computed as the…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 3/5: - The learned model can"Part 3/5: The learned model can then be used in a fitted value iteration algorithm to approximate the optimal value function without discretizing the state space. Fitted…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 2/5: - Discretization works reasonably well"Part 2/5: Discretization works reasonably well for small, low-dimensional state spaces (e.g. 2-4 dimensions), but becomes impractical for higher dimensional problems.…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 1/5: # Applying Reinforcement Learning to"Part 1/5: Applying Reinforcement Learning to Continuous State MDPs Discretization and its Limitations Reinforcement learning can be applied to continuous state MDPs…conscript in #leofinance • 2 hours ago@conscript "This video has already been summarized: https://inleo.io/thre..."This video has already been summarized:ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 4/4: One challenge in reinforcement learning"Part 4/4: One challenge in reinforcement learning is the exploration-exploitation tradeoff. A purely greedy policy that always takes the currently estimated best action may get…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 3/4: π^*(s) = argmax_a R(s,a) +"Part 3/4: π^ (s) = argmax_a R(s,a) + γ * Σ_s' P(s'|s,a) * V^ (s') Learning State Transition Probabilities In practice, the state transition probabilities P(s'|s,a) may…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 2/4: The value function satisfies Bellman's"Part 2/4: The value function satisfies Bellman's equation: V^π(s) = R(s) + γ * Σ_s' P(s'|s,π(s)) * V^π(s') This equation states that the value of a state is the immediate…ai-summaries in #leofinance • 2 hours ago@ai-summaries "Part 1/4: ## Reinforcement Learning: Markov Decision"Part 1/4: Reinforcement Learning: Markov Decision Processes and Value Iteration Recap of Markov Decision Processes (MDPs) In the previous lecture, we introduced the concept…
