Metadata
Title
Subject:Reinforcement Learning
Category
courses
UUID
023b0169050c4ce88334c9f0673173b3
Source URL
https://projects.scss.tcd.ie/subject_area/reinforcement-learning/
Parent URL
https://projects.scss.tcd.ie
Crawl Time
2026-03-16T07:02:17+00:00
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Subject:Reinforcement Learning

Source: https://projects.scss.tcd.ie/subject_area/reinforcement-learning/ Parent: https://projects.scss.tcd.ie

Reinforcement learning (RL) and especially deep reinforcement learning have emerged as powerful paradigms for learning quasi-optimal sequential decision making strategies (in applications as diverse as game playing and urban traffic control). RL uses an approach based on’ trial and error’ in which agents learn by interacting with their environment. Most RL algorithms assume that the … Read more

Poor travel-time reliability, meaning that travel times for the same journey are highly variable and unpredictable, gives rise to similar negative impacts on the environment and the economy as does traffic congestion. Moreover, being able to offer a high degree of travel-time reliability will facilitate the uptake of sustainable road transportation including future public, shared, … Read more

An ideal bus route would offer highly predictable journey times to travellers so that the same journey taken at the same time of day on different occasions would take the same amount of time. While there are many sources of variability in journey times such as traffic conditions, passenger boarding and offloading time, and the … Read more

This project will investigate the use of reinforcement learning to develop a highway journey booking system incorporating a dynamic pricing strategy to allow traffic demand to be shaped in ways that will improve traffic efficiency and enhance sustainability by reducing emissions and fuel consumption. The goal will be to evaluate the potential benefit of the … Read more