1 code implementation • EMNLP 2021 • Subhajit Chaudhury, Prithviraj Sen, Masaki Ono, Daiki Kimura, Michiaki Tatsubori, Asim Munawar
We outline a method for end-to-end differentiable symbolic rule learning and show that such symbolic policies outperform previous state-of-the-art methods in text-based RL for the coin collector environment from 5-10x fewer training games.
no code implementations • 27 Oct 2023 • Toshihiro Takahashi, Takaaki Tateishi, Michiaki Tatsubori
Semantic text similarity plays an important role in software engineering tasks in which engineers are requested to clarify the semantics of descriptive labels (e. g., business terms, table column names) that are often consists of too short or too generic words and appears in their IT systems.
1 code implementation • 5 Jul 2023 • Subhajit Chaudhury, Sarathkrishna Swaminathan, Daiki Kimura, Prithviraj Sen, Keerthiram Murugesan, Rosario Uceda-Sosa, Michiaki Tatsubori, Achille Fokoue, Pavan Kapanipathi, Asim Munawar, Alexander Gray
Text-based reinforcement learning agents have predominantly been neural network-based models with embeddings-based representation, learning uninterpretable policies that often do not generalize well to unseen games.
no code implementations • 6 Jun 2023 • Yeldar Toleubay, Don Joven Agravante, Daiki Kimura, Baihan Lin, Djallel Bouneffouf, Michiaki Tatsubori
The proposed system addresses the lack of explainability of current Neural Network models and provides a more trustworthy solution for mental disorder diagnosis.
1 code implementation • 29 Nov 2022 • Tsunehiko Tanaka, Daiki Kimura, Michiaki Tatsubori
We propose a novel agent, DiffG-RL, which constructs a Difference Graph that organizes the environment states and common sense by means of interactive objects with a dedicated graph encoder.
no code implementations • 19 Oct 2022 • Tsunehiko Tanaka, Daiki Kimura, Michiaki Tatsubori
They are usually imperfect information games, and their interactions are only in the textual modality.
no code implementations • 1 Mar 2022 • Michiaki Tatsubori, Takao Moriyama, Tatsuya Ishikawa, Paolo Fraccaro, Anne Jones, Blair Edwards, Julian Kuehnert, Sekou L. Remy
When providing the boundary conditions for hydrological flood models and estimating the associated risk, interpolating precipitation at very high temporal resolutions (e. g. 5 minutes) is essential not to miss the cause of flooding in local regions.
1 code implementation • ACL 2021 • Daiki Kimura, Subhajit Chaudhury, Masaki Ono, Michiaki Tatsubori, Don Joven Agravante, Asim Munawar, Akifumi Wachi, Ryosuke Kohita, Alexander Gray
We present Logical Optimal Actions (LOA), an action decision architecture of reinforcement learning applications with a neuro-symbolic framework which is a combination of neural network and symbolic knowledge acquisition approach for natural language interaction games.
no code implementations • EMNLP 2021 • Daiki Kimura, Masaki Ono, Subhajit Chaudhury, Ryosuke Kohita, Akifumi Wachi, Don Joven Agravante, Michiaki Tatsubori, Asim Munawar, Alexander Gray
Deep reinforcement learning (RL) methods often require many trials before convergence, and no direct interpretability of trained policies is provided.
no code implementations • 24 Sep 2021 • Zhanhong Yang, Satoshi Masuda, Michiaki Tatsubori
The experiments also showed that we can calibrate a corresponding DM in a virtual testing environment with up to 26% more accuracy than with fixed calibration methods.
no code implementations • 3 Mar 2021 • Daiki Kimura, Subhajit Chaudhury, Akifumi Wachi, Ryosuke Kohita, Asim Munawar, Michiaki Tatsubori, Alexander Gray
Specifically, we propose an integrated method that enables model-free reinforcement learning from external knowledge sources in an LNNs-based logical constrained framework such as action shielding and guide.
no code implementations • 26 Oct 2020 • Thomas Carta, Subhajit Chaudhury, Kartik Talamadupula, Michiaki Tatsubori
The goal is to force an RL agent to use both text and visual features to predict natural language action commands for solving the final task of cooking a meal.
1 code implementation • EMNLP 2020 • Subhajit Chaudhury, Daiki Kimura, Kartik Talamadupula, Michiaki Tatsubori, Asim Munawar, Ryuki Tachibana
Our bootstrapped agent shows improved generalization in solving unseen TextWorld games, using 10x-20x fewer training games compared to previous state-of-the-art methods despite requiring less number of training episodes.
no code implementations • 17 Dec 2019 • Michiaki Tatsubori, Asim Munawar, Takao Moriyama
Planning is a critical component of any artificial intelligence system that concerns the realization of strategies or action sequences typically for intelligent agents and autonomous robots.
1 code implementation • 21 Aug 2018 • Takao Moriyama, Giovanni De Magistris, Michiaki Tatsubori, Tu-Hoa Pham, Asim Munawar, Ryuki Tachibana
Common approaches to control a data-center cooling system rely on approximated system/environment models that are built upon the knowledge of mechanical cooling and electrical and thermal management.
Systems and Control