1 code implementation • EMNLP (ArgMining) 2021 • Rafael Mestre, Razvan Milicin, Stuart Middleton, Matt Ryan, Jiatong Zhu, Timothy J. Norman
In this paper, we present M-Arg, a multimodal argument mining dataset with a corpus of US 2020 presidential debates, annotated through crowd-sourced annotations.
1 code implementation • 18 Feb 2024 • Tesfay Zemuy Gebrekidan, Sebastian Stein, Timothy J. Norman
Task offloading in MEC is a strategy that meets the demands of UDs by distributing tasks between UDs and MEC servers.
1 code implementation • 1 Nov 2019 • Paolo Pareti, George Konstantinidis, Timothy J. Norman, Murat Şensoy
On the one hand, SHACL constraints can be used to define a "schema" for graph datasets.
1 code implementation • 25 Dec 2023 • Xingzhou Lou, Junge Zhang, Timothy J. Norman, Kaiqi Huang, Yali Du
We propose Topology-based multi-Agent Policy gradiEnt (TAPE) for both stochastic and deterministic MAPG methods.
1 code implementation • 7 Feb 2024 • Gregory Everett, Ryan Beal, Tim Matthews, Timothy J. Norman, Sarvapali D. Ramchurn
In this paper, we present a novel sequential team selection model in soccer.
no code implementations • 13 Jun 2017 • Federico Cerutti, Alice Toniolo, Timothy J. Norman
In this paper we provide a first analysis of the research questions that arise when dealing with the problem of communicating pieces of formal argumentation through natural language interfaces.
no code implementations • 19 Nov 2013 • Federico Cerutti, Alice Toniolo, Nir Oren, Timothy J. Norman
Computational trust mechanisms aim to produce trust ratings from both direct and indirect information about agents' behaviour.
1 code implementation • 2 Jul 2019 • Paolo Pareti, George Konstantinidis, Timothy J. Norman, Murat Şensoy
Output schemas model the graphs that would be obtained by running the rules on the graph models of the input schema.
no code implementations • 15 Nov 2019 • Paolo Pareti, George Konstantinidis, Timothy J. Norman
An important use of sensors and actuator networks is to comply with health and safety policies in hazardous environments.
no code implementations • 23 Mar 2020 • Ryan Beal, Georgios Chalkiadakis, Timothy J. Norman, Sarvapali D. Ramchurn
In this paper we present a novel approach to optimise tactical and strategic decision making in football (soccer).
no code implementations • 31 Aug 2020 • Paolo Pareti, George Konstantinidis, Fabio Mogavero, Timothy J. Norman
We study the interaction of SHACL features in this logic and provide the detailed map of decidability and complexity results of the aforementioned decision problems for different SHACL sublanguages.
no code implementations • 8 Dec 2020 • Ryan Beal, Stuart E. Middleton, Timothy J. Norman, Sarvapali D. Ramchurn
In this paper, we present a new application-focused benchmark dataset and results from a set of baseline Natural Language Processing and Machine Learning models for prediction of match outcomes for games of football (soccer).
no code implementations • 18 Feb 2021 • Ryan Beal, Georgios Chalkiadakis, Timothy J. Norman, Sarvapali D. Ramchurn
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 across a given time frame.
no code implementations • 5 Oct 2022 • Mohammad Divband Soorati, Enrico H. Gerding, Enrico Marchioni, Pavel Naumov, Timothy J. Norman, Sarvapali D. Ramchurn, Bahar Rastegari, Adam Sobey, Sebastian Stein, Danesh Tarpore, Vahid Yazdanpanah, Jie Zhang
The Agents, Interaction and Complexity research group at the University of Southampton has a long track record of research in multiagent systems (MAS).
no code implementations • 14 Oct 2022 • Zhaori Guo, Timothy J. Norman, Enrico H. Gerding
In this paper, we propose a more effective interactive reinforcement learning system by introducing multiple trainers, namely Multi-Trainer Interactive Reinforcement Learning (MTIRL), which could aggregate the binary feedback from multiple non-perfect trainers into a more reliable reward for an agent training in a reward-sparse environment.
no code implementations • 13 Feb 2023 • Gregory Everett, Ryan J. Beal, Tim Matthews, Joseph Early, Timothy J. Norman, Sarvapali D. Ramchurn
By imputing player locations from easy to obtain event data, we increase the accessibility of downstream tasks.
no code implementations • 12 May 2023 • 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.
no code implementations • 15 May 2023 • Zhaori Guo, Timothy J. Norman, Enrico H. Gerding
In practice, however, gathering answers from a set of advisors has a cost.
no code implementations • 10 Oct 2023 • Olaf Lipinski, Adam J. Sobey, Federico Cerutti, Timothy J. Norman
As humans, we use linguistic elements referencing time, such as before or tomorrow, to easily share past experiences and future predictions.