Markov Decision Processes

A Hidden Markov Model of Customer Relationship Dynamics: DSA ADS Course - 2023

On 11 Nov, 2022 By admin 0 Comments

DSA ADS Course - 2023

Discuss enabling marketers to dynamically segment their customer base and to examine methods by which the firm can alter long-term buying behavior.

Discuss dynamics of customer relationships using typical transaction data.

The proposed method/model permits not only capturing the dynamics of customer relationships, but also incorporating the effect of the sequence of customer-firm encounters on the dynamics of customer relationships and the subsequent buying behavior.

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Reinforcement Learning under Partial Observability Guided by Learned Environment Models

On 25 Jun, 2022 By admin 0 Comments

June, 2022

Abstract

In practical applications, we can rarely assume full observability of a system's environment, despite such knowledge being important for determining a reactive control system's precise interaction with its environment. Therefore, we propose an approach for reinforcement learning (RL) in partially observable environments. While assuming that the environment behaves like a partially observable Markov decision process with known discrete actions, we assume no knowledge about its structure or transition probabilities.

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