Interdisciplinary Workshop on Mechanical Intelligence: Summary Report

Fuente: arXiv
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Autores principales: Webster-Wood, Victoria A., Gravish, Nicholas, Alavi, Amir, Arrieta, Andres F, Bergbreiter, Sarah, Bloch, Anthony, Blumenschein, Laura, Cao, C. Chase, Carter, Aja Mia, Celli, Paolo, Chen, Tony, Coad, Margaret, Cutkosky, Mark, Dickey, Michael, Do, Brian, Full, Robert, Haghshenas-Jaryani, Mahdi, Jayaram, Kaushik, Johnson, Aaron, Kanso, Eva, Lejeune, Emma, Li, Chen, Li, Suyi, Lipton, Jeffrey, MacCurdy, Rob, McHenry, Matt, Mongeau, Jean-Michel, Murphey, Todd, Plecnik, Mark, Raney, Jordan, Sochol, Ryan D., Stuart, Hannah, Temel, Zeynep, Tolley, Michael, Trimmer, Barry, Wallin, T. J., Wang, Kon-Well, Yan, Wenzhong, Yim, Mark, Zhang, Wenlong
Formato: Preprint
Publicado: 2026
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author Webster-Wood, Victoria A.
Gravish, Nicholas
Alavi, Amir
Arrieta, Andres F
Bergbreiter, Sarah
Bloch, Anthony
Blumenschein, Laura
Cao, C. Chase
Carter, Aja Mia
Celli, Paolo
Chen, Tony
Coad, Margaret
Cutkosky, Mark
Dickey, Michael
Do, Brian
Full, Robert
Haghshenas-Jaryani, Mahdi
Jayaram, Kaushik
Johnson, Aaron
Kanso, Eva
Lejeune, Emma
Li, Chen
Li, Suyi
Lipton, Jeffrey
MacCurdy, Rob
McHenry, Matt
Mongeau, Jean-Michel
Murphey, Todd
Plecnik, Mark
Raney, Jordan
Sochol, Ryan D.
Stuart, Hannah
Temel, Zeynep
Tolley, Michael
Trimmer, Barry
Wallin, T. J.
Wang, Kon-Well
Yan, Wenzhong
Yim, Mark
Zhang, Wenlong
author_facet Webster-Wood, Victoria A.
Gravish, Nicholas
Alavi, Amir
Arrieta, Andres F
Bergbreiter, Sarah
Bloch, Anthony
Blumenschein, Laura
Cao, C. Chase
Carter, Aja Mia
Celli, Paolo
Chen, Tony
Coad, Margaret
Cutkosky, Mark
Dickey, Michael
Do, Brian
Full, Robert
Haghshenas-Jaryani, Mahdi
Jayaram, Kaushik
Johnson, Aaron
Kanso, Eva
Lejeune, Emma
Li, Chen
Li, Suyi
Lipton, Jeffrey
MacCurdy, Rob
McHenry, Matt
Mongeau, Jean-Michel
Murphey, Todd
Plecnik, Mark
Raney, Jordan
Sochol, Ryan D.
Stuart, Hannah
Temel, Zeynep
Tolley, Michael
Trimmer, Barry
Wallin, T. J.
Wang, Kon-Well
Yan, Wenzhong
Yim, Mark
Zhang, Wenlong
contents This report provides a summary of the outcomes of the Interdisciplinary Workshop on Mechanical Intelligence held in 2024. Mechanical Intelligence (MI) represents the phenomenon that novel structural features of material/biological/robotic systems can encode intelligence through responsiveness, adaptivity, memory, and learning in the mechanical structure itself. This is in contrast to computational intelligence, wherein the intelligence functions occur through electrical signaling and computer code. The two-day workshop was held at NSF headquarters on May 30-31 and included 38 invited academic researcher participants, and 8 program officers from the NSF. The workshop was structured around active small and large group discussions in groups of 4-5 and 9-10 with the goal of addressing topical questions on MI. Working groups entered notes into shared presentation slides for each discussion session and presented their outcomes in a final presentation on the last day. Here we summarize the overall outcomes of the workshop.
format Preprint
id arxiv_https___arxiv_org_abs_2604_16381
institution arXiv
publishDate 2026
record_format arxiv
spellingShingle Interdisciplinary Workshop on Mechanical Intelligence: Summary Report
Webster-Wood, Victoria A.
Gravish, Nicholas
Alavi, Amir
Arrieta, Andres F
Bergbreiter, Sarah
Bloch, Anthony
Blumenschein, Laura
Cao, C. Chase
Carter, Aja Mia
Celli, Paolo
Chen, Tony
Coad, Margaret
Cutkosky, Mark
Dickey, Michael
Do, Brian
Full, Robert
Haghshenas-Jaryani, Mahdi
Jayaram, Kaushik
Johnson, Aaron
Kanso, Eva
Lejeune, Emma
Li, Chen
Li, Suyi
Lipton, Jeffrey
MacCurdy, Rob
McHenry, Matt
Mongeau, Jean-Michel
Murphey, Todd
Plecnik, Mark
Raney, Jordan
Sochol, Ryan D.
Stuart, Hannah
Temel, Zeynep
Tolley, Michael
Trimmer, Barry
Wallin, T. J.
Wang, Kon-Well
Yan, Wenzhong
Yim, Mark
Zhang, Wenlong
Robotics
This report provides a summary of the outcomes of the Interdisciplinary Workshop on Mechanical Intelligence held in 2024. Mechanical Intelligence (MI) represents the phenomenon that novel structural features of material/biological/robotic systems can encode intelligence through responsiveness, adaptivity, memory, and learning in the mechanical structure itself. This is in contrast to computational intelligence, wherein the intelligence functions occur through electrical signaling and computer code. The two-day workshop was held at NSF headquarters on May 30-31 and included 38 invited academic researcher participants, and 8 program officers from the NSF. The workshop was structured around active small and large group discussions in groups of 4-5 and 9-10 with the goal of addressing topical questions on MI. Working groups entered notes into shared presentation slides for each discussion session and presented their outcomes in a final presentation on the last day. Here we summarize the overall outcomes of the workshop.
title Interdisciplinary Workshop on Mechanical Intelligence: Summary Report
topic Robotics
url https://arxiv.org/abs/2604.16381