Marc Pickett
Impact in
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- Reinforcement Learning in Robotics
- Evolutionary Algorithms and Applications
- Domain Adaptation and Few-Shot Learning
- AI-based Problem Solving and Planning
- Machine Learning and Algorithms
Papers in
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- AI-based Problem Solving and Planning 3
- Topic Modeling 3
- Semantic Web and Ontologies 3
- Advanced Text Analysis Techniques 2
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- Human-Automation Interaction and Safety 3
- Co-authors
- Andrew G. Barto (1 shared paper)David W. Aha (5 shared papers)J. Gregory Trafton (2 shared papers)Constance Heitmeyer (2 shared papers)M. Caccia (1 shared paper)Vincenzo Lomonaco (1 shared paper)German I. Parisi (1 shared paper)Issam Laradji (1 shared paper)
- Journals
- Clinical Genetics (1 paper)Automated Software Engineering (1 paper)Cognitive Science (1 paper)Lecture notes in computer science (1 paper)Biologically Inspired Cognitive Architectures (1 paper)
- Partner nations
- United StatesJapanCanada
In The Last Decade
Marc Pickett
12 papers receiving 120 citations
Peers
Comparison fields: 5 of 50
- Artificial Intelligence 87
- Software 9
- Computer Vision and Pattern Recognition 23
- Computational Theory and Mathematics 18
- Hardware and Architecture 5
Countries citing papers authored by Marc Pickett
This map shows the geographic impact of Marc Pickett's research. It shows the number of citations coming from papers published by authors working in each country. You can also color the map by specialization and compare the number of citations received by Marc Pickett with the expected number of citations based on a country's size and research output (numbers larger than one mean the country cites Marc Pickett more than expected).
Fields of papers citing papers by Marc Pickett
This network shows the impact of papers produced by Marc Pickett. Nodes represent research fields, and links connect fields that are likely to share authors. Colored nodes show fields that tend to cite the papers produced by Marc Pickett. The network helps show where Marc Pickett may publish in the future.
Co-authors
The 22 scholars most cited alongside Marc Pickett, linked wherever they have co-authored with each other. Click a name or a connecting line to browse the papers they share.
All Works
| # | Work | ||
|---|---|---|---|
| 1 | PolicyBlocks: An Algorithm for Creating Useful Macro-Actions in Reinforcement Learning | 2002 | 63 |
| 2 | 2022 | 28 | |
| 3 | 2014 | 13 | |
| 4 | 2013 | 4 | |
| 5 | 2005 | 4 | |
| 6 | 2009 | 4 | |
| 7 | 2013 | 4 | |
| 8 | Spontaneous Analogy by Piggybacking on a Perceptual System | 2013 | 3 |
| 9 | Acquiring User Models to Test Automated Assistants | 2013 | 2 |
| 10 | The Übercruncher: concept formation by analogy discovery | 2007 | 1 |
| 11 | 2025 | 1 | |
| 12 | Essential Phenomena of General Intelligence | 2008 | 1 |
| 13 | Models of Strategic Deficiency and Poker | 2007 | 0 |
| 14 | Building on deep learning | 2013 | 0 |
About Marc Pickett
Marc Pickett is a scholar working on Artificial Intelligence, Social Psychology, Surgery, Cognitive Neuroscience and Cultural Studies, having authored 14 papers that have together received 128 indexed citations. Recurring topics across this work include AI-based Problem Solving and Planning (3 papers), Topic Modeling (3 papers), Semantic Web and Ontologies (3 papers), Human-Automation Interaction and Safety (3 papers), Language and cultural evolution (2 papers), Healthcare Technology and Patient Monitoring (2 papers), Advanced Text Analysis Techniques (2 papers) and Neural dynamics and brain function (2 papers). The work is most often cited by research in Artificial Intelligence (87 citations), Software (9 citations), Computer Vision and Pattern Recognition (23 citations), Computational Theory and Mathematics (18 citations) and Hardware and Architecture (5 citations). Marc Pickett has collaborated with scholars based in United States, Japan and Canada. Frequent co-authors include Andrew G. Barto, David W. Aha, J. Gregory Trafton, Constance Heitmeyer, M. Caccia, Vincenzo Lomonaco, German I. Parisi, Issam Laradji, Myla Archer and Nikhil Churamani. Their work appears in journals such as Clinical Genetics, Automated Software Engineering, Cognitive Science, Lecture notes in computer science and Biologically Inspired Cognitive Architectures.
Rankless uses publication and citation data sourced from OpenAlex, an open and comprehensive bibliographic database. While OpenAlex provides broad and valuable coverage of the global research landscape, it—like all bibliographic datasets—has inherent limitations. These include incomplete records, variations in author disambiguation, differences in journal indexing, and delays in data updates. As a result, some metrics and network relationships displayed in Rankless may not fully capture the entirety of a scholar's output or impact.