Asset Selling Problems

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Dynamic Programming: Optimal Control

Explores Dynamic Programming for optimal control, focusing on stability, stationary policy, and recursive solutions.

Market Regulation: External Benefits and Subsidies

Examines market regulation, focusing on external benefits and the effects of subsidies on equilibrium price and quantity.

Stochastic Optimal Control: Martingale Theorem

Explores Stochastic Optimal Control, emphasizing Optimal Consumption and Investment, the Martingale Representation Theorem, and the Verification Theorem.

Controlled Stochastic Processes

Explores controlled stochastic processes, focusing on analysis, behavior, and optimization, using dynamic programming to solve real-world problems.

Markov Decision Processes: Foundations of Reinforcement Learning

Covers Markov Decision Processes, their structure, and their role in reinforcement learning.

Asset Selling Problem

Explores the Asset Selling Problem to maximize long-term reward without a deadline.

Asset Selling: Optimal Revenue Policy

Explores asset selling dynamics, optimal revenue policy, acceptance thresholds, and commodity price impact.

Advanced Machine Learning: Discrete Reinforcement Learning

Introduces the basics of Reinforcement Learning, covering discrete states, actions, policies, value functions, MDPs, and optimal policies.

Dynamic Programming: Optimal Decision Making

Explores dynamic programming for optimizing decision-making processes over time, using real-world examples like oil extraction and stock trading.

Market Failures: Negative Externalities

Explores market failures due to negative externalities and distorted incentives, offering strategies for addressing these issues.