7 citations · 15 across the 11 of their papers we have counts for
12 papers
MADDM: Multi-Advisor Dynamic Binary Decision-Making by Maximizing the Utility
Zhaori Guo, Timothy J. Norman, Enrico H. Gerding
Being able to infer ground truth from the responses of multiple imperfect advisors is a problem of crucial importance in many decision-making applications, such as lending, trading…
PRIME: A Price-Reverting Impact Model of a cryptocurrency Exchange
Christopher J. Cho, Timothy J. Norman, Manuel Nunes
In a financial exchange, market impact is a measure of the price change of an asset following a transaction. This is an important element of market microstructure, which determines…
Inferring Player Location in Sports Matches: Multi-Agent Spatial Imputation from Limited Observations
Gregory Everett, Ryan J. Beal, Tim Matthews +3
Understanding agent behaviour in Multi-Agent Systems (MAS) is an important problem in domains such as autonomous driving, disaster response, and sports analytics. Existing MAS prob…
Multi-trainer Interactive Reinforcement Learning System
Zhaori Guo, Timothy J. Norman, Enrico H. Gerding
Interactive reinforcement learning can effectively facilitate the agent training via human feedback. However, such methods often require the human teacher to know what is the corre…
From Intelligent Agents to Trustworthy Human-Centred Multiagent Systems
Mohammad Divband Soorati, Enrico H. Gerding, Enrico Marchioni +9
The Agents, Interaction and Complexity research group at the University of Southampton has a long track record of research in multiagent systems (MAS). We have made substantial sci…
Optimising Long-Term Outcomes using Real-World Fluent Objectives: An Application to Football
Ryan Beal, Georgios Chalkiadakis, Timothy J. Norman +1
In this paper, we present a novel approach for optimising long-term tactical and strategic decision-making in football (soccer) by encapsulating events in a league environment acro…