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Recurrent neural networks are used to forecast time series in finance, climate, language, and from many other domains. Reservoir computers are a particularly easily trainable form of recurrent neural network. Recently, a “next-generation” reservoir computer was introduced in which the memory trace involves only a finite number of previous symbols. The inherent limitations of finite-past memory traces are explored in this proposal.
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The hypothesis explored is that collective intelligence is not only the province of groups of animals, and that an important symmetry exists between the behavioral science of swarms and the competencies of cells and other biological systems at different scales. The implications of this approach are outlined, as is the possible impact of tools from the field of diverse intelligence for regenerative medicine and synthetic bioengineering.
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Humans frequently interact with agents whose intentions can fluctuate between competition and cooperation over time. It is unclear how the brain adapts to fluctuating intentions of others when the nature of the interactions (to cooperate or compete) is not explicitly and truthfully signaled. Here, model-based fMRI and a task in which participants thought they were playing with another player are used.
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Self-oscillations are the result of an efficient mechanism generating periodic motion from a constant power source. In quantum devices, these oscillations may arise due to the interaction between single electron dynamics and mechanical motion. This research shows that, due to the complexity of this mechanism, these self-oscillations may irrupt, vanish, or exhibit a bistable behavior causing hysteresis cycles.
Projects
The project explores the adaptive wisdom that individuals from different cultures and religious groups across 12 countries apply in their everyday lives.