We negotiate every day in our life for a number of activities ranging from deciding the wake-up time in the morning, the number of hours to spend on our coursework, a destination for our next holiday to the number of bucks to be spent on our desirable gadgets. How great it would be if there … full description “An Automated Negotiating Agent using GENIUS (completed)”
Category: Artificial Intelligence
Building a chatbot for student queries (available)
It is important that student queries are replied to quickly and accurately. Many of the requests for information are fully explained in resources such as the student handbook. These include questions such as where students request extensions on coursework or how shuold they inform College if they are absent from a lecture. Frequently these questions … full description “Building a chatbot for student queries (available)”
Building a Full Causality Chain Across an Enterprise System (completed)
Data Provenance refers to records of the inputs, entities, systems and process that influence data of interest, providing a historical record of the data and its origins. To provide a holistic view of the data provenance in an enterprise system, the provenance records of the activities carried out on a client workstation is important. Last … full description “Building a Full Causality Chain Across an Enterprise System (completed)”
Computer Vision for Extreme Environments (available)
The use of data from extreme environments in computer vision have shown an increase of interest in recent years as drones and autonomous vehicles were introduced into new uses. Nuclear plants, deep underwater and space vehicles are some of the areas computer vision can be applied to develop a fully autonomous system. Furthermore, the development … full description “Computer Vision for Extreme Environments (available)”
Cybercrime and ransomware groups – data analysis (available)
Project background Cybersecurity is the practice of defending computers, servers, mobile devices, electronic systems, networks, and data from malicious attacks, in an ever increasingly complex threat landscape. These attacks constitute a variety of computer-enabled and computer-dependent crimes, broadly categorised as ‘cybercrime’. In order to be in a position to defend against these attacks and minimise … full description “Cybercrime and ransomware groups – data analysis (available)”
Deep learning based underwater image enhancement and object recognition (available)
In the past decade, advances in marine object recognition have been dramatically boosted for monitoring of underwater ecosystems. Traditional statistical analysis and ocean model simulation heavily depend on the availability of visual features. However, Due to light attenuation and scattering problem, the underwater images captured by optical imaging system are heavily degraded. As a result, … full description “Deep learning based underwater image enhancement and object recognition (available)”
Deep Learning-based Environmental Sound Classification (available)
Automatic sound classification attracts increasing research attention owing to its vast applications, such as robot navigation, environmental sensing, musical instrument classification, medical diagnosis, and surveillance. Sound classification tasks involve the extraction of acoustic characteristics from the audio signals and the subsequent identification of different sound classes. The broad range of sound classification deployments can be … full description “Deep Learning-based Environmental Sound Classification (available)”
Digital Humans in a Virtual Reality Football Platform. (available)
Libero is a VR football platform; a ground-breaking experience in visitor focused, immersive content that allows fans to truly live the history of famous football clubs, whilst also giving them a glimpse of what the future holds. Using A.I., world-class animation and award-winning storytelling, we can engage fans, new and old, in a way that … full description “Digital Humans in a Virtual Reality Football Platform. (available)”
Federated Machine Learning – Security and Privacy Evaluation Framework (available)
Project Description User data is essential for many of the modern business operations, especially related to the building consumer segmentation and profiling – for marketing and services personalisation. Dealing with user data has its positive and negatives, especially after the General Data Protection Regulation (GDPR) collecting and storing user’s personal data. Centralised machine learning approaches … full description “Federated Machine Learning – Security and Privacy Evaluation Framework (available)”
Interactive Visualisation of Disentangled Representations (completed)
This project aims to develop an interactive visualisation toolkit based on existing technologies (IPython & Plotly) that will assist researchers in debugging and understanding complex models in the area of representation learning. Representation learning is a sub-field of machine learning that focuses on developing techniques for representing objects that exist in high-dimensional space (e.g. faces … full description “Interactive Visualisation of Disentangled Representations (completed)”
Local Search Heuristics for Schelling Games on Graphs (completed)
Schelling games were recently introduced and studied as a novel class of strategic games inspired by the Schelling’s model of residential segregation. These games are played on an undirected graph that represent the topology of a residential area. In addition, we are given a set of agents partitioned into multiple types. Each agent occupies a … full description “Local Search Heuristics for Schelling Games on Graphs (completed)”
Machine Learning for Crystal Structure Prediction (completed)
Crystal Structure Prediction (CSP) is one of the major problems in computational chemistry with numerous applications in real life. This is essentially the (global) minimisation of a continuous, high-dimensional, complicated function. Many heuristic methods have been proposed for CSP and recently new methods based on Machine Learning were introduced. The goal of this project is … full description “Machine Learning for Crystal Structure Prediction (completed)”
Mixed Nash Equilibria in Net Coordination Games (completed)
Net Coordination Games form a special class of many-player games with several applications in Theoretical Computer Sciene, Multi Agent Systems, and Semi Supervised Learning. Nash equilibria correspond to the stable outcomes and they are the prominent solution concept in games. It is known that Net Coordination Games possess a pure Nash equilibrium, but unfortunately, it … full description “Mixed Nash Equilibria in Net Coordination Games (completed)”
Presenting Agent Simulation Experiments in COGNISIM (available)
When we simulate a system or a process, we normally want to imitate its operation over time. This need arises in a variety of contexts, from engineering to testing, training, education and video games. We are interested in simulation models that involve modeling human systems to gain an understanding of how they behave over time. … full description “Presenting Agent Simulation Experiments in COGNISIM (available)”
Python and Unreal Engine 4 integration (completed)
This challenging project aims to integrate a Python-based agent framework that has been developed at RHUL with Unreal Engine 4 (UE4). With recent successes in reinforcement learning and other online learning approaches there has been much work on developing environments to test new and state of the art algorithms. UE4 provides the perfect development environment … full description “Python and Unreal Engine 4 integration (completed)”