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03/01/2022
AI Planning Annotation for Sample Efficient Reinforcement Learning
AI planning and Reinforcement Learning (RL) both solve sequential decisi...
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01/18/2022
Combining Fast and Slow Thinking for Human-like and Efficient Navigation in Constrained Environments
Current AI systems lack several important human capabilities, such as ad...
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10/05/2021
Thinking Fast and Slow in AI: the Role of Metacognition
AI systems have seen dramatic advancement in recent years, bringing many...
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12/03/2020
Circles are like Ellipses, or Ellipses are like Circles? Measuring the Degree of Asymmetry of Static and Contextual Embeddings and the Implications to Representation Learning
Human judgments of word similarity have been a popular method of evaluat...
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11/25/2020
Continual learning with direction-constrained optimization
This paper studies a new design of the optimization algorithm for traini...
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10/19/2020
Deriving Commonsense Inference Tasks from Interactive Fictions
Commonsense reasoning simulates the human ability to make presumptions a...
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10/08/2020
Text-based RL Agents with Commonsense Knowledge: New Challenges, Environments and Baselines
Text-based games have emerged as an important test-bed for Reinforcement...
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10/05/2020
Interactive Fiction Game Playing as Multi-Paragraph Reading Comprehension with Reinforcement Learning
Interactive Fiction (IF) games with real human-written natural language ...
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06/16/2020
A Study of Compositional Generalization in Neural Models
Compositional and relational learning is a hallmark of human intelligenc...
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04/06/2020
Learning to Recover Reasoning Chains for Multi-Hop Question Answering via Cooperative Games
We propose the new problem of learning to recover reasoning chains from ...
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09/17/2019
Simple yet Effective Bridge Reasoning for Open-Domain Multi-Hop Question Answering
A key challenge of multi-hop question answering (QA) in the open-domain ...
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06/05/2019
Teaching AI to Explain its Decisions Using Embeddings and Multi-Task Learning
Using machine learning in high-stakes applications often requires predic...
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03/11/2019
Hybrid Reinforcement Learning with Expert State Sequences
Existing imitation learning approaches often require that the complete d...
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03/07/2019
Learning Hierarchical Teaching in Cooperative Multiagent Reinforcement Learning
Heterogeneous knowledge naturally arises among different agents in coope...
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11/12/2018
TED: Teaching AI to Explain its Decisions
Artificial intelligence systems are being increasingly deployed due to t...
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09/21/2018
Interpretable Multi-Objective Reinforcement Learning through Policy Orchestration
Autonomous cyber-physical agents and systems play an increasingly large ...
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05/29/2018
Teaching Meaningful Explanations
The adoption of machine learning in high-stakes applications such as hea...
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05/20/2018
Learning to Teach in Cooperative Multiagent Reinforcement Learning
We present a framework and algorithm for peer-to-peer teaching in cooper...
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12/11/2017
The Eigenoption-Critic Framework
Eigenoptions (EOs) have been recently introduced as a promising idea for...
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11/14/2017
Evidence Aggregation for Answer Re-Ranking in Open-Domain Question Answering
A popular recent approach to answering open-domain questions is to first...
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10/30/2017
Eigenoption Discovery through the Deep Successor Representation
Options in reinforcement learning allow agents to hierarchically decompo...
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09/27/2016