scholarly journals Growing simulated robots with environmental feedback

Author(s):  
Kathryn Walker ◽  
Helmut Hauser ◽  
Sebastian Risi
2021 ◽  
Vol 121 ◽  
pp. 68-77
Author(s):  
Meghna N Marjadi ◽  
Lauren Drakopulos ◽  
Lian W. Guo ◽  
J. Zachary Koehn ◽  
Sarita V. Panchang ◽  
...  

2019 ◽  
Vol 3 (2) ◽  
pp. 254-259 ◽  
Author(s):  
Yu Kawano ◽  
Lulu Gong ◽  
Brian D. O. Anderson ◽  
Ming Cao

F1000Research ◽  
2021 ◽  
Vol 9 ◽  
pp. 34
Author(s):  
Stefan T. Arold

Longstanding scientific efforts have been dedicated to answer why and how our particular intelligence is generated by our brain but not by the brain of other species. However, surprisingly little effort has been made to ask why no other species ever developed an intelligence similar to ours. Here, I explore this question based on genetic and paleontologic evidence. Contrary to the established view, this review suggests that the developmental hurdles alone are not high enough to explain the uniqueness of human intelligence (HI). As an additional explanation I propose that HI is normally not retained by natural selection, because it is, under most conditions, an intrinsically unfavourable trait. This unfavourableness, however, cannot be explained by physical constraints alone; rather, it may also be rooted in the same emotional and social complexity that is necessary for the development of HI. Thus, a major obstacle towards HI may not be solely the development of the required physical assets, but also to cope with harmful individual, social and environmental feedback intrinsically associated with this trait.


2018 ◽  
Vol 204 ◽  
pp. 19-26 ◽  
Author(s):  
Yulin Tang ◽  
Huaijia Xin ◽  
Shu Yang ◽  
Meiting Guo ◽  
Tyler Malkoske ◽  
...  

2019 ◽  
Vol 27 (5) ◽  
pp. 285-294 ◽  
Author(s):  
Frederike Kubandt ◽  
Michael Nowak ◽  
Tim Koglin ◽  
Claudius Gros ◽  
Bulcsú Sándor

Which kind of complex behavior may arise from self-organizing principles? We investigate this question for the case of snake-like robots composed of passively coupled segments, with every segment containing two wheels actuated separately by a single neuron. The robot is self-organized both on the level of the individual wheels and with respect to inter-wheel coordination, which arises exclusively from the mechanical coupling of the individual wheels and segments. For the individual wheel, the generating principle proposed results in locomotive states that correspond to self-organized limit cycles of the sensorimotor loop. Our robot interacts with the environment by monitoring the state of its actuators, that is, via propriosensation. External sensors are absent. In a structured environment the robot shows complex emergent behavior that includes pushing movable blocks around, reversing direction when hitting a wall, and turning when climbing a slope. On flat grounds the robot wiggles in a snake-like manner, when moving at higher velocities. We also investigate the emergence of motor primitives, namely, the route to locomotion, which is characterized by a series of local and global bifurcations in terms of dynamical system theory.


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