[HTML][HTML] Applications of reinforcement learning in energy systems
ATD Perera, P Kamalaruban - Renewable and Sustainable Energy …, 2021 - Elsevier
Energy systems undergo major transitions to facilitate the large-scale penetration of
renewable energy technologies and improve efficiencies, leading to the integration of many …
renewable energy technologies and improve efficiencies, leading to the integration of many …
Neural approaches to conversational AI
This tutorial surveys neural approaches to conversational AI that were developed in the last
few years. We group conversational systems into three categories:(1) question answering …
few years. We group conversational systems into three categories:(1) question answering …
Recent advances and challenges in task-oriented dialog systems
Due to the significance and value in human-computer interaction and natural language
processing, task-oriented dialog systems are attracting more and more attention in both …
processing, task-oriented dialog systems are attracting more and more attention in both …
Recsim: A configurable simulation platform for recommender systems
We propose RecSim, a configurable platform for authoring simulation environments for
recommender systems (RSs) that naturally supports sequential interaction with users …
recommender systems (RSs) that naturally supports sequential interaction with users …
Comparative study of model-based and model-free reinforcement learning control performance in HVAC systems
Reinforcement learning (RL) shows the potential to address drawbacks of rule-based control
and model predictive control and exhibits great effectiveness in heating, ventilation and air …
and model predictive control and exhibits great effectiveness in heating, ventilation and air …
Pseudo Dyna-Q: A reinforcement learning framework for interactive recommendation
Applying reinforcement learning (RL) in recommender systems is attractive but costly due to
the constraint of the interaction with real customers, where performing online policy learning …
the constraint of the interaction with real customers, where performing online policy learning …
Model-based reinforcement learning for biological sequence design
The ability to design biological structures such as DNA or proteins would have considerable
medical and industrial impact. Doing so presents a challenging black-box optimization …
medical and industrial impact. Doing so presents a challenging black-box optimization …
Query resolution for conversational search with limited supervision
In this work we focus on multi-turn passage retrieval as a crucial component of
conversational search. One of the key challenges in multi-turn passage retrieval comes from …
conversational search. One of the key challenges in multi-turn passage retrieval comes from …
Large sequence models for sequential decision-making: a survey
Transformer architectures have facilitated the development of large-scale and general-
purpose sequence models for prediction tasks in natural language processing and computer …
purpose sequence models for prediction tasks in natural language processing and computer …
Evaluating conversational recommender systems via user simulation
Conversational information access is an emerging research area. Currently, human
evaluation is used for end-to-end system evaluation, which is both very time and resource …
evaluation is used for end-to-end system evaluation, which is both very time and resource …