Asimov's Coming Back

Ever since the word ‘ROBOT’ first appeared in a science\ud fiction in 1921, scientists and engineers have been trying\ud different ways to create it. Present technologies in\ud mechanical and electrical engineering makes it possible\ud to have robots in such places as industrial manufacturing\ud and assembling lines. Although they are\ud essentially robotic arms or similarly driven by electrical\ud power and signal control, they could be treated the\ud primitive pioneers in application. Researches in the\ud laboratories go much further. Interdisciplines are\ud directing the evolution of more advanced robots. Among these are artificial\ud intelligence, computational neuroscience, mathematics and robotics. These disciplines\ud come closer as more complex problems emerge.\ud From a robot’s point of view, three basic abilities are needed. They are thinking\ud and memory, sensory perceptions, control and behaving. These are capabilities we\ud human beings have to adapt ourselves to the environment. Although\ud researches on robots, especially on intelligent thinking, progress slowly, a revolution\ud for biological inspired robotics is spreading out in the laboratories all over the world

Linear combination of one-step predictive information with an external reward in an episodic policy gradient setting: a critical analysis

One of the main challenges in the field of embodied artificial intelligence is the open-ended autonomous learning of complex behaviours. Our approach is to use task-independent, information-driven intrinsic motivation(s) to support task-dependent learning. The work presented here is a preliminary step in which we investigate the predictive information (the mutual information of the past and future of the sensor stream) as an intrinsic drive, ideally supporting any kind of task acquisition. Previous experiments have shown that the predictive information (PI) is a good candidate to support autonomous, open-ended learning of complex behaviours, because a maximisation of the PI corresponds to an exploration of morphology- and environment-dependent behavioural regularities. The idea is that these regularities can then be exploited in order to solve any given task. Three different experiments are presented and their results lead to the conclusion that the linear combination of the one-step PI with an external reward function is not generally recommended in an episodic policy gradient setting. Only for hard tasks a great speed-up can be achieved at the cost of an asymptotic performance lost

On Neuromechanical Approaches for the Study of Biological Grasp and Manipulation

Biological and robotic grasp and manipulation are undeniably similar at the level of mechanical task performance. However, their underlying fundamental biological vs. engineering mechanisms are, by definition, dramatically different and can even be antithetical. Even our approach to each is diametrically opposite: inductive science for the study of biological systems vs. engineering synthesis for the design and construction of robotic systems. The past 20 years have seen several conceptual advances in both fields and the quest to unify them. Chief among them is the reluctant recognition that their underlying fundamental mechanisms may actually share limited common ground, while exhibiting many fundamental differences. This recognition is particularly liberating because it allows us to resolve and move beyond multiple paradoxes and contradictions that arose from the initial reasonable assumption of a large common ground. Here, we begin by introducing the perspective of neuromechanics, which emphasizes that real-world behavior emerges from the intimate interactions among the physical structure of the system, the mechanical requirements of a task, the feasible neural control actions to produce it, and the ability of the neuromuscular system to adapt through interactions with the environment. This allows us to articulate a succinct overview of a few salient conceptual paradoxes and contradictions regarding under-determined vs. over-determined mechanics, under- vs. over-actuated control, prescribed vs. emergent function, learning vs. implementation vs. adaptation, prescriptive vs. descriptive synergies, and optimal vs. habitual performance. We conclude by presenting open questions and suggesting directions for future research. We hope this frank assessment of the state-of-the-art will encourage and guide these communities to continue to interact and make progress in these important areas

Dual tasking in Parkinson's disease: cognitive consequences while walking

Published in final edited form as: Neuropsychology. 2017 September; 31(6): 613–623. doi:10.1037/neu0000331.OBJECTIVE: Cognitive deficits are common in Parkinson's disease (PD) and exacerbate the functional limitations imposed by PD's hallmark motor symptoms, including impairments in walking. Though much research has addressed the effect of dual cognitive-locomotor tasks on walking, less is known about their effect on cognition. The purpose of this study was to investigate the relation between gait and executive function, with the hypothesis that dual tasking would exacerbate cognitive vulnerabilities in PD as well as being associated with gait disturbances. METHOD: Nineteen individuals with mild-moderate PD without dementia and 13 age- and education-matched normal control adults (NC) participated. Executive function (set-shifting) and walking were assessed singly and during dual tasking. RESULTS: Dual tasking had a significant effect on cognition (reduced set-shifting) and on walking (speed, stride length) for both PD and NC, and also on stride frequency for PD only. The impact of dual tasking on walking speed and stride frequency was significantly greater for PD than NC. Though the group by condition interaction was not significant, PD had fewer set-shifts than NC on dual task. Further, relative to NC, PD showed significantly greater variability in cognitive performance under dual tasking, whereas variability in motor performance remained unaffected by dual tasking. CONCLUSIONS: Dual tasking had a significantly greater effect in PD than in NC on cognition as well as on walking. The results suggest that assessment and treatment of PD should consider the cognitive as well as the gait components of PD-related deficits under dual-task conditions. (PsycINFO Database Record)