Tom's Blog

In this paper, we successfully established a solvable bargaining model and shows the source of negotiation power. We build a two-round bargaining model with both-side uncertainty to study the negotiation power. We construct a Sequential Equilibrium for this game and characterize it by an ordinary differential equation. Due to the computational difficulty of the SE solution, we further find a feasible but almost the same good solution, Optimal Commitment. Under this solution, we restate the strat ...

Introduction Appointment systems are wildly used is people's daily life. They are used in the scenario that people's demand can be known in advance, for example, hospitals, barbershops, and government departments. Appointment systems help balance the trade-off between the waiting time and the service utilization. However, a bad design can lead to catastrophe in which the waiting time is extremely long. People are unsatisfied when they have to waiting for a long time even if they have made a app ...

Introduction Reinforcement learning (RL) is a powerful learning paradigm for sequential decision making under uncertainty. However, RL agents sometimes do not perform well in reality since there are some different between reality and the simulator. There are many difference between deployment environment and training environment. such as friction, obstacles, human behavior, etc. Moreover, there are natural or deliberate disturbances in the environment sometimes, which make agents more difficult ...

This study was done with my classmate Haike Xu as the final project of Mathematical Model of Smart City in 2019 summer. I transcribed our poster and slides into the blog article trying to inspire more people who are interested in this topic. Introduction Background In the real world, the transmission of a message is often indirect, passing through a complex base station network. However, due to some reasons, the network may contain noises which will disturb the message and make it inaccurate ...