no code implementations • 19 May 2023 • Shiyao Ding, Takayuki Ito
In this paper, we propose Self-Agreement, a novel framework for fine-tuning LLMs to autonomously find agreement using data generated by LLM itself.
no code implementations • 15 Dec 2022 • Rafik Hadfi, Ahmed Moustafa, Kai Yoshino, Takayuki Ito
We address this limitation using a novel method for predicting the best answers using the questioner's background information and other features, such as the textual content or the relationships with other participants.
no code implementations • 30 May 2022 • Ryuta Arisaka, Ryoma Nakai, Yusuke Kawamoto, Takayuki Ito
We present core formal constraints for the theme aspect argumentation model and then more formal constraints that improve its fallacy identification capability.
no code implementations • 1 Sep 2021 • Pankaj Mishra, Ahmed Moustafa, Takayuki Ito
In this work, we focus on resource allocation in a decentralised open market.
no code implementations • 22 Jul 2021 • Muhammad Asad, Ahmed Moustafa, Takayuki Ito
Despite significant convergence, this training involves several privacy threats on participants' data when shared with the central cloud server.
no code implementations • 26 Apr 2021 • Ryuta Arisaka, Takayuki Ito
In this paper, we propose a fresh perspective on argumentation semantics, to view them as a relational database.
no code implementations • 17 Apr 2021 • Qin Liang, Minjie Zhang, Fenghui Ren, Takayuki Ito
Trust evaluation is an important topic in both research and applications in sociable environments.
no code implementations • 27 Jan 2021 • Jiaqi Wu, Weihua Li, Quan Bai, Takayuki Ito, Ahmed Moustafa
A large amount of information has been published to online social networks every day.
no code implementations • 22 Jul 2020 • Ryuta Arisaka, Takayuki Ito
In this context, there is a more recently proposed formalism of may-must argumentation (MMA) that enforces still local but more abstract labelling conditions.
no code implementations • 6 Apr 2020 • Muhammad Asad, Ahmed Moustafa, Takayuki Ito, Muhammad Aslam
These amounts of data are suitable for training different learning models.
no code implementations • 23 Jan 2020 • Ryuta Arisaka, Takayuki Ito
A negotiation process by 2 agents e1 and e2 can be interleaved by another negotiation process between, say, e1 and e3.
no code implementations • 16 Jan 2020 • Ryuta Arisaka, Takayuki Ito
In this work, we contemplate a way of broadening it by accommodating may- and must- conditions for an argument to be accepted or rejected, as determined by the number(s) of rejected and accepted attacking arguments.
no code implementations • 9 Sep 2019 • Ryuta Arisaka, Makoto Hagiwara, Takayuki Ito
From marketing to politics, exploitation of incomplete information through selective communication of arguments is ubiquitous.
no code implementations • 28 Oct 2017 • Susel Fernandez, Takayuki Ito
In this work we propose an ontology to support automated negotiation in multiagent systems.
1 code implementation • 1 Jun 2016 • Rafik Hadfi, Takayuki Ito
We propose a holonic multiagent simulator that can simulate any complex urban environment.
1 code implementation • 15 Oct 2015 • Rafik Hadfi, Sho Tokuda, Takayuki Ito
One of its advantages is that it can represent the uncertainty of the traffic states and the changing travel demand and supply conditions.
1 code implementation • 1 Jul 2015 • Rafik Hadfi, Takayuki Ito
We evaluate the model experimentally using parameterized nonlinear utility spaces, showing that it can handle a large family of complex utility spaces by finding optimal contracts, outperforming previous sampling-based approaches.
1 code implementation • 1 Dec 2014 • Rafik Hadfi, Takayuki Ito
Additionally, it leads us to a potential parametric model that could be used for opponent modeling in complex non-linear negotiations.