Search Results for author:
Found 5 papers, 2 papers with code
Deep Reinforcement Learning for Solving Management Problems: Towards A Large Management Mode
We introduce a deep reinforcement learning (DRL) approach for solving management problems including inventory management, dynamic pricing, and recommendation.
Improving Generalization in Task-oriented Dialogues with Workflows and Action Plans
We perform extensive experiments on the Action-Based Conversations Dataset (ABCD) with T5-small, base and large models, and show that such models: a) are able to more readily generalize to unseen workflows by following the provided plan, and b) are able to generalize to executing unseen actions if they are provided in the plan.
Dual Contrastive Prediction for Incomplete Multi-view Representation Learning
In this article, we propose a unified framework to solve the following two challenging problems in incomplete multi-view representation learning: i) how to learn a consistent representation unifying different views, and ii) how to recover the missing views.
pyRDDLGym: From RDDL to Gym Environments
We present pyRDDLGym, a Python framework for auto-generation of OpenAI Gym environments from RDDL declerative description.
Robustness-Driven Exploration with Probabilistic Metric Temporal Logic
However, algorithms for autonomous exploration often focus on optimizing time and coverage in a greedy fashion.
