16 citations · 68 across the 12 of their papers we have counts for
13 papers
Modeling Moral Choices in Social Dilemmas with Multi-Agent Reinforcement Learning
Elizaveta Tennant, Stephen Hailes, Mirco Musolesi
Practical uses of Artificial Intelligence (AI) in the real world have demonstrated the importance of embedding moral choices into intelligent agents. They have also highlighted tha…
Graph Neural Modeling of Network Flows
Victor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi
Network flow problems, which involve distributing traffic such that the underlying infrastructure is used effectively, are ubiquitous in transportation and logistics. Among them, t…
Dynamic Network Reconfiguration for Entropy Maximization using Deep Reinforcement Learning
Christoffel Doorman, Victor-Alexandru Darvariu, Stephen Hailes +1
A key problem in network theory is how to reconfigure a graph in order to optimize a quantifiable objective. Given the ubiquity of networked systems, such work has broad practical…
Trust-based Consensus in Multi-Agent Reinforcement Learning Systems
Ho Long Fung, Victor-Alexandru Darvariu, Stephen Hailes +1
An often neglected issue in multi-agent reinforcement learning (MARL) is the potential presence of unreliable agents in the environment whose deviations from expected behavior can…
Planning Spatial Networks with Monte Carlo Tree Search
Victor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi
We tackle the problem of goal-directed graph construction: given a starting graph, a budget of modifications, and a global objective function, the aim is to find a set of edges who…
Solving Graph-based Public Good Games with Tree Search and Imitation Learning
Victor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi
Public goods games represent insightful settings for studying incentives for individual agents to make contributions that, while costly for each of them, benefit the wider society.…
Cooperation and Reputation Dynamics with Reinforcement Learning
Nicolas Anastassacos, Julian García, Stephen Hailes +1
Creating incentives for cooperation is a challenge in natural and artificial systems. One potential answer is reputation, whereby agents trade the immediate cost of cooperation for…
Identifying Vulnerabilities of Industrial Control Systems using Evolutionary Multiobjective Optimisation
Nilufer Tuptuk, Stephen Hailes
In this paper we propose a novel methodology to assist in identifying vulnerabilities in a real-world complex heterogeneous industrial control systems (ICS) using two evolutionary…
Goal-directed graph construction using reinforcement learning
Victor-Alexandru Darvariu, Stephen Hailes, Mirco Musolesi
Graphs can be used to represent and reason about systems and a variety of metrics have been devised to quantify their global characteristics. However, little is currently known abo…
Partner Selection for the Emergence of Cooperation in Multi-Agent Systems Using Reinforcement Learning
Nicolas Anastassacos, Stephen Hailes, Mirco Musolesi
Social dilemmas have been widely studied to explain how humans are able to cooperate in society. Considerable effort has been invested in designing artificial agents for social dil…
Online Collective Animal Movement Activity Recognition
Kehinde Owoeye, Stephen Hailes
Learning the activities of animals is important for the purpose of monitoring their welfare vis a vis their behaviour with respect to their environment and conspecifics. While prev…
Real-Time Stochastic Optimal Control for Multi-agent Quadrotor Systems
Vicenç Gómez, Sep Thijssen, Andrew Symington +2
This paper presents a novel method for controlling teams of unmanned aerial vehicles using Stochastic Optimal Control (SOC) theory. The approach consists of a centralized high-leve…
A Bayesian Residual-Based Test for Cointegration
Thomas Furmston, Stephen Hailes, A. Jennifer Morton
Cointegration is an important concept in the analysis of non-stationary time-series, giving conditions under which a collection of non-stationary processes has an underlying statio…