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02/01/2022
Planner-Reasoner Inside a Multi-task Reasoning Agent
We consider the problem of multi-task reasoning (MTR), where an agent ca...
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01/24/2022
TOPS: Transition-based VOlatility-controlled Policy Search and its Global Convergence
Risk-averse problems receive far less attention than risk-neutral contro...
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08/13/2021
TDM: Trustworthy Decision-Making via Interpretability Enhancement
Human-robot interactive decision-making is increasingly becoming ubiquit...
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09/14/2020
Variance-Reduced Off-Policy Memory-Efficient Policy Search
Off-policy policy optimization is a challenging problem in reinforcement...
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06/06/2020
Stable and Efficient Policy Evaluation
Policy evaluation algorithms are essential to reinforcement learning due...
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09/18/2019
A Human-Centered Data-Driven Planner-Actor-Critic Architecture via Logic Programming
Recent successes of Reinforcement Learning (RL) allow an agent to learn ...
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06/17/2019
PACMAN: A Planner-Actor-Critic Architecture for Human-Centered Planning and Learning
Conventional reinforcement learning (RL) allows an agent to learn polici...
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05/16/2019
Knowledge-Based Sequential Decision-Making Under Uncertainty
Deep reinforcement learning (DRL) algorithms have achieved great success...
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10/31/2018
SDRL: Interpretable and Data-efficient Deep Reinforcement Learning Leveraging Symbolic Planning
Deep reinforcement learning (DRL) has gained great success by learning d...
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10/31/2018
SDRL: Interpretable and Data-efficient Deep Reinforcement LearningLeveraging Symbolic Planning
Deep reinforcement learning (DRL) has gained great success by learning d...
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09/07/2018
A Block Coordinate Ascent Algorithm for Mean-Variance Optimization
Risk management in dynamic decision problems is a primary concern in man...
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04/20/2018
PEORL: Integrating Symbolic Planning and Hierarchical Reinforcement Learning for Robust Decision-Making
Reinforcement learning and symbolic planning have both been used to buil...
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04/17/2017
