Markov Decision Processes

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

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.

Reinforcement Learning under Partial Observability Guided by Learned Environment Models

June, 2022


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.