Asset Selling Problem

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Covers infinite-horizon problems in Applied Probability and Stochastic Processes.

Discusses policy iteration and linear programming methods for solving Markov Decision Processes.

Covers algorithmic complexity and travel time analysis, focusing on measuring the time taken by algorithms and evaluating their performance.

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

Explores practical aspects of solving parity games, including winning strategies, algorithms, complexity, determinism, and heuristic approaches.

Covers decision-making in marketing based on customer behavior for optimal strategies.

Explores accelerating the Value Iteration algorithm using control theory and matrix splitting techniques to achieve faster convergence.

Explores the Extra-Gradient method for Primal-dual optimization, covering nonconvex-concave problems, convergence rates, and practical performance.

Explores algorithm correctness, worst-case complexity analysis, and efficiency comparison based on input size.

Explores linear systems, convergence, and solving methods with a focus on CPU time and memory requirements.