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pro vyhledávání: '"Joel Schooler"'
Autor:
Mark Stefik, Michael Youngblood, Peter Pirolli, Christian Lebiere, Robert Thomson, Robert Price, Lester D. Nelson, Robert Krivacic, Jacob Le, Konstantinos Mitsopoulos, Sterling Somers, Joel Schooler
Publikováno v:
Applied AI Letters, Vol 2, Iss 4, Pp n/a-n/a (2021)
Abstract COGLE (COmmon Ground Learning and Explanation) is an explainable artificial intelligence (XAI) system where autonomous drones deliver supplies to field units in mountainous areas. The mission risks vary with topography, flight decisions, and
Externí odkaz:
https://doaj.org/article/cfa16c2b8b144e01856c7c3dab30c09a
Autor:
Mark J. Stefik, Peter Pirolli, Joel Schooler, Konstantinos Mitsopoulos, Sterling Somers, Robert T. Krivacic, Robert Price, Jacob Le, Lester D. Nelson, Christian Lebiere, Michael Youngblood, Robert Thompson
Publikováno v:
Applied AI Letters, Vol 2, Iss 4, Pp n/a-n/a (2021)
COGLE (COmmon Ground Learning and Explanation) is an explainable artificial intelligence (XAI) system for autonomous drones that deliver supplies in mountainous areas to field units. The drone missions have risks that vary with topography, flight dec
Autor:
Sterling Somers, Joel Schooler, Peter Pirolli, Christian Lebiere, Konstantinos Mitsopoulos, Robert Thomson
Publikováno v:
Topics in cognitive scienceReferences. 14(4)
We argue that cognitive models can provide a common ground between human users and deep reinforcement learning (Deep RL) algorithms for purposes of explainable artificial intelligence (AI). Casting both the human and learner as cognitive models provi