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pro vyhledávání: '"Johanson, Michael Bradley"'
Advances in artificial intelligence often stem from the development of new environments that abstract real-world situations into a form where research can be done conveniently. This paper contributes such an environment based on ideas inspired by ele
Externí odkaz:
http://arxiv.org/abs/2205.06760
Autor:
Pilarski, Patrick M., Butcher, Andrew, Davoodi, Elnaz, Johanson, Michael Bradley, Brenneis, Dylan J. A., Parker, Adam S. R., Acker, Leslie, Botvinick, Matthew M., Modayil, Joseph, White, Adam
Learned communication between agents is a powerful tool when approaching decision-making problems that are hard to overcome by any single agent in isolation. However, continual coordination and communication learning between machine agents or human-m
Externí odkaz:
http://arxiv.org/abs/2203.09498
Autor:
Butcher, Andrew, Johanson, Michael Bradley, Davoodi, Elnaz, Brenneis, Dylan J. A., Acker, Leslie, Parker, Adam S. R., White, Adam, Modayil, Joseph, Pilarski, Patrick M.
In this paper, we contribute a multi-faceted study into Pavlovian signalling -- a process by which learned, temporally extended predictions made by one agent inform decision-making by another agent. Signalling is intimately connected to time and timi
Externí odkaz:
http://arxiv.org/abs/2201.03709
Autor:
Brenneis, Dylan J. A., Parker, Adam S., Johanson, Michael Bradley, Butcher, Andrew, Davoodi, Elnaz, Acker, Leslie, Botvinick, Matthew M., Modayil, Joseph, White, Adam, Pilarski, Patrick M.
Artificial intelligence systems increasingly involve continual learning to enable flexibility in general situations that are not encountered during system training. Human interaction with autonomous systems is broadly studied, but research has hither
Externí odkaz:
http://arxiv.org/abs/2112.07774