1 citations · 1 across the 4 of their papers we have counts for
4 papers
Self-evolving Autoencoder Embedded Q-Network
J. Senthilnath, Bangjian Zhou, Zhen Wei Ng +7
In the realm of sequential decision-making tasks, the exploration capability of a reinforcement learning (RL) agent is paramount for achieving high rewards through interactions wit…
Evolving Restricted Boltzmann Machine-Kohonen Network for Online Clustering
J. Senthilnath, Adithya Bhattiprolu, Ankur Singh +4
A novel online clustering algorithm is presented where an Evolving Restricted Boltzmann Machine (ERBM) is embedded with a Kohonen Network called ERBM-KNet. The proposed ERBM-KNet e…
S-REINFORCE: A Neuro-Symbolic Policy Gradient Approach for Interpretable Reinforcement Learning
Rajdeep Dutta, Qincheng Wang, Ankur Singh +3
This paper presents a novel RL algorithm, S-REINFORCE, which is designed to generate interpretable policies for dynamic decision-making tasks. The proposed algorithm leverages two…
Shall We Trust All Relational Tuples by Open Information Extraction? A Study on Speculation Detection
Kuicai Dong, Aixin Sun, Jung-Jae Kim +1
Open Information Extraction (OIE) aims to extract factual relational tuples from open-domain sentences. Downstream tasks use the extracted OIE tuples as facts, without examining th…