Surprise Maximization: A Dynamic Programming Approach

TL;DR

This paper introduces a dynamic programming method to solve the surprise maximization problem, offering an alternative to the convex analysis approach and making the solution more accessible.

Contribution

The paper presents a new dynamic programming approach to solve the surprise maximization problem, simplifying the derivation of the optimal solution.

Findings

Dynamic programming effectively solves the surprise maximization problem.

The new approach simplifies understanding compared to convex analysis methods.

The method provides an accessible alternative for deriving optimal solutions.

Abstract

Borwein et al. (2000) solved a surprise maximization problem by applying results from convex analysis and mathematical programming. Although, their proof is elegant, it requires advanced knowledge from both areas to understand it. Here, we provide another approach to derive an optimal solution of the problem by utilizing dynamic programming.