activity
20092026
most citedInterpretable Multi-Objective Reinforcement Learning through Policy Orchestration

23 citations · 173 across the 34 of their papers we have counts for

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Showing 2018 · cs.AIShow all

5 papers · 2 filters

cs.AI2018

Building Ethically Bounded AI

Francesca Rossi, Nicholas Mattei

The more AI agents are deployed in scenarios with possibly unexpected situations, the more they need to be flexible, adaptive, and creative in achieving the goal we have given them…

cs.AI2018

Incorporating Behavioral Constraints in Online AI Systems

Avinash Balakrishnan, Djallel Bouneffouf, Nicholas Mattei +1

AI systems that learn through reward feedback about the actions they take are increasingly deployed in domains that have significant impact on our daily life. However, in many case…

cs.AI2018★ 12 cited

Answering Science Exam Questions Using Query Rewriting with Background Knowledge

Ryan Musa, Xiaoyan Wang, Achille Fokoue +6

Open-domain question answering (QA) is an important problem in AI and NLP that is emerging as a bellwether for progress on the generalizability of AI methods and techniques. Much o…

cs.AI2018★ 16 cited

Improving Natural Language Inference Using External Knowledge in the Science Questions Domain

Xiaoyan Wang, Pavan Kapanipathi, Ryan Musa +8

Natural Language Inference (NLI) is fundamental to many Natural Language Processing (NLP) applications including semantic search and question answering. The NLI problem has gained…

cs.AI2018

A Systematic Classification of Knowledge, Reasoning, and Context within the ARC Dataset

Michael Boratko, Harshit Padigela, Divyendra Mikkilineni +10

The recent work of Clark et al. introduces the AI2 Reasoning Challenge (ARC) and the associated ARC dataset that partitions open domain, complex science questions into an Easy Set…