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researcher

J. Shah

39 papers hereh-index 468.4k citations181 works total

Matching runs newest-first, so older work may not be attached to this profile yet.

author position
  • middle author12
  • last author26

Across the 38 of 39 papers where every author was matched, so the position is known.

fields
  • cs.RO12
  • cs.AI9
  • cs.LG9
  • cs.CL5
  • cs.CY1
  • cs.MA1
same name
  • J. Shah — 16 papers, h 10
  • J. Shah — 4 papers, h 26
  • J. Shah — 3 papers, h 5
  • J. Shah — 3 papers, h 12
  • J. Shah — 3 papers, h 13
  • J. Shah — 3 papers, h 2

Either other researchers who publish under this name, or the same person where the external sources have not merged their records.

identity via Semantic Scholar / OpenAlex

activity
20132023
most citedArtificial Intelligence and Life in 2030: The One Hundred Year Study on Artificial Intelligence

153 citations · 716 across the 39 of their papers we have counts for

collaborators
Showing 2019Show all

4 papers · 1 filter

cs.CL2019★ 20 cited

Learning Household Task Knowledge from WikiHow Descriptions

Yilun Zhou, Julie A. Shah, Steven Schockaert

Commonsense procedural knowledge is important for AI agents and robots that operate in a human environment. While previous attempts at constructing procedural knowledge are mostly…

cs.MA2019

On Memory Mechanism in Multi-Agent Reinforcement Learning

Yilun Zhou, Derrik E. Asher, Nicholas R. Waytowich +1

Multi-agent reinforcement learning (MARL) extends (single-agent) reinforcement learning (RL) by introducing additional agents and (potentially) partial observability of the environ…

cs.RO2019★ 17 cited

Planning With Uncertain Specifications (PUnS)

Ankit Shah, Shen Li, Julie Shah

Reward engineering is crucial to high performance in reinforcement learning systems. Prior research into reward design has largely focused on Markovian functions representing the r…

cs.CL2019★ 8 cited

Predicting ConceptNet Path Quality Using Crowdsourced Assessments of Naturalness

Yilun Zhou, Steven Schockaert, Julie A. Shah

In many applications, it is important to characterize the way in which two concepts are semantically related. Knowledge graphs such as ConceptNet provide a rich source of informati…

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Not affiliated with arXiv. Researcher data from Semantic Scholar (ODC-BY) and OpenAlex.