Search Results for author:
Found 9 papers, 1 papers with code
Planning with Logical Graph-based Language Model for Instruction Generation
Despite the superior performance of large language models to generate natural language texts, it is hard to generate texts with correct logic according to a given task, due to the difficulties for neural models to capture implied rules from free-form texts.
Sequential Condition Evolved Interaction Knowledge Graph for Traditional Chinese Medicine Recommendation
Traditional Chinese Medicine (TCM) has a rich history of utilizing natural herbs to treat a diversity of illnesses.
A Hierarchical Temporal Planning-Based Approach for Dynamic Hoist Scheduling Problems
Hoist scheduling has become a bottleneck in electroplating industry applications with the development of autonomous devices.
Learning Visual Planning Models from Partially Observed Images
Although a number of approaches have been developed for learning planning models from fully observed unstructured data (e. g., images), in many scenarios raw observations are often incomplete.
Integrating AI Planning with Natural Language Processing: A Combination of Explicit and Tacit Knowledge
Natural language processing (NLP) aims at investigating the interactions between agents and humans, processing and analyzing large amounts of natural language data.
Text-Based Action-Model Acquisition for Planning
Specifically, we first build a novel language model to extract plan traces from texts, and then build a set of constraints to generate action models based on the extracted plan traces.
Creativity of AI: Hierarchical Planning Model Learning for Facilitating Deep Reinforcement Learning
Despite of achieving great success in real-world applications, Deep Reinforcement Learning (DRL) is still suffering from three critical issues, i. e., data efficiency, lack of the interpretability and transferability.
Retrosynthetic Planning with Experience-Guided Monte Carlo Tree Search
In retrosynthetic planning, the huge number of possible routes to synthesize a complex molecule using simple building blocks leads to a combinatorial explosion of possibilities.
Ranked #3 on
Multi-step retrosynthesis
on USPTO-190
Gradient-Based Mixed Planning with Symbolic and Numeric Action Parameters
In this paper, we propose a novel algorithm framework to solve numeric planning problems mixed with logical relations and numeric changes based on gradient descent.
