A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Filters
When the goal is to generate a series of activities: A self-organized simulated robot arm
[article]
2019
arXiv
pre-print
Preserved Fulltext
We believe that our approach may be generalized to generate self-organized sequences of activities in general. ...
We study the emergence of autonomous task switching for the case of a simulated robot arm. Grasping one of several moving objects corresponds in this setting to a specific activity. ...
Conclusion One of the biggest challenges in the design of controllers for autonomous agents is the combination of different goal oriented behaviors into a series of self-organized activities [36] . ...
arXiv:1905.07235v1
fatcat:a3os6rsnvbgt5lvv6udcq73u2e
When the goal is to generate a series of activities: A self-organized simulated robot arm
2019
PLoS ONE
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
We believe that our approach may be generalized to generate self-organized sequences of activities in general. ...
We study the emergence of autonomous task switching for the case of a simulated robot arm. Grasping one of several moving objects corresponds in this setting to a specific activity. ...
Conclusion One of the biggest challenges in the design of controllers for autonomous agents is the combination of different goal oriented behaviors into a series of self-organized activities [36] . ...
doi:10.1371/journal.pone.0217004
pmid:31216272
pmcid:PMC6584010
fatcat:3alm3u7cwzc3tcqumis3rykvh4
Active learning of inverse models with intrinsically motivated goal exploration in robots
2013
Robotics and Autonomous Systems
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2015; you can also visit the original URL.
The file type is application/pdf.
Other Versions
We introduce the Self-Adaptive Goal Generation - Robust Intelligent Adaptive Curiosity (SAGG-RIAC) architecture as an intrinsi- cally motivated goal exploration mechanism which allows active learning of ...
This allows a robot to efficiently and actively learn distributions of parameterized motor skills/policies that solve a corresponding distribution of parameterized tasks/goals. ...
Acknowledgment We thank everyone who gave us their feedback on the paper. This research was partially funded by ERC Grant EXPLOR-ERS 240007 ...
doi:10.1016/j.robot.2012.05.008
fatcat:hb7lzdcgergujekl4fi4zfsxza
Active exploration for body model learning through self-touch on a humanoid robot with artificial skin
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
In this work, we present an embodied computational model on a simulated humanoid robot with artificial sensitive skin on large areas of its body. ...
The mechanisms of infant development are far from understood. Learning about one's own body is likely a foundation for subsequent development. ...
The observation space is the robot skin-activation generated when the robot contacts its torso or face with its arm. This is a discrete space of individual taxels and their activation. ...
arXiv:2008.13483v1
fatcat:vlbkg5jie5dtpobcr7z3f5bg3e
R-IAC: Robust Intrinsically Motivated Exploration and Active Learning
2009
IEEE Transactions on Autonomous Mental Development
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
Intelligent adaptive curiosity (IAC) was initially introduced as a developmental mechanism allowing a robot to self-organize developmental trajectories of increasing complexity without preprogramming the ...
to IAC in a complex sensorimotor space where only a small subspace is neither unlearnable nor trivial. ...
ACKNOWLEDGMENT The authors would like to thank M. Li for his crucial help in the elaboration and evaluation of the ILO-GMR regression algorithm. ...
doi:10.1109/tamd.2009.2037513
fatcat:m52j25t6xbdmzn25wpecazsnge
Active inference and robot control: a case study
2016
Journal of the Royal Society Interface
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
Here, we discuss a proof-of-principle implementation of the active inference scheme for the control or the 7-DoF arm of a (simulated) PR2 robot. ...
In the discussion, we consider the potential importance of being able to implement active inference in robots. ...
Active inference starts from the fundaments of self-organization which suggests that any adaptive agent needs to maintain its biophysical states within limits, therefore maintaining a generalized homeostasis ...
doi:10.1098/rsif.2016.0616
pmid:27683002
pmcid:PMC5046960
fatcat:abrywa7iijes5ihprd3rrvj27e
Intrinsically Motivated Exploration for Developmental and Active Sensorimotor Learning
[chapter]
2010
Studies in Computational Intelligence
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2016; you can also visit the original URL.
The file type is application/pdf.
Finally, an open-source accompanying software containing these algorithms as well as tools to reproduce all the experiments in simulation presented in this paper is made publicly available. ...
Then, we introduce a novel formulation of IAC, called R-IAC, and show that its performances as an intrinsically motivated active learning algorithm are far superior to IAC in a complex sensorimotor space ...
Acknowledgements The work presented here was partly realized and supported by the Sony CSL Laboratory, Paris, France (the Playground Experiment in particular), and partly realized and supported by INRIA ...
doi:10.1007/978-3-642-05181-4_6
fatcat:233hqi2zx5cypeqthc7hvhsgrq
Modular active curiosity-driven discovery of tool use
2016
2016 IEEE/RSJ International Conference on Intelligent Robots and Systems (IROS)
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2018; you can also visit the original URL.
The file type is application/pdf.
MB exploits efficiently a modular representation of the space of parameterized problems/effects. We also study an active version of Model Babbling (the MACOB architecture). ...
In particular, we consider goal babbling architectures that were designed to explore and learn solutions to fields of sensorimotor problems, i.e. to acquire inverse models mapping a space of parameterized ...
Experimental setup We designed a robotic setup where a 2D simulated arm can grasp two sticks that can be used to move some of the out-of-reach objects (see Fig.2 ). ...
doi:10.1109/iros.2016.7759584
dblp:conf/iros/ForestierO16
fatcat:bvbbra73rfconof6lktkwnydxy
Revisiting active perception
2017
Autonomous Robots
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
The history of these ideas, perhaps selective due to our perspectives, is presented with the goal of organizing the past literature and highlighting the seminal contributions. ...
Despite the recent successes in robotics, artificial intelligence and computer vision, a complete artificial agent necessarily must include active perception. ...
Active Perception systems attempt to deal with the perceptual-motor loop of a robot in a real environment, rejecting simulated worlds. ...
doi:10.1007/s10514-017-9615-3
pmid:31983809
pmcid:PMC6954017
fatcat:oqx5jim2frdtjpvz5kh4q22uuq
Revisiting Active Perception
[article]
2016
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2019; you can also visit the original URL.
The file type is application/pdf.
Note that this fulltext copy is not of the "primary" version of this work. The version it corresponds to is:
2016 pre-print arXiv:1603.02729v1 fatcat:tz4hu2u33nbmlpxtw4arzbadhu
The history of these ideas, perhaps selective due to our perspectives, is presented with the goal of organizing the past literature and highlighting the seminal contributions. ...
Despite the recent successes in robotics, artificial intelligence and computer vision, a complete artificial agent necessarily must include active perception. ...
Active Perception systems attempt to deal with the perceptual-motor loop of a robot in a real environment, rejecting simulated worlds. ...
arXiv:1603.02729v2
fatcat:wnt362piu5g4flvf7tkqz6ncd4
Robot Learning by Active Imitation
[chapter]
2007
Humanoid Robots, Human-like Machines
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
TIN2005-01359, and by the European Robotics Research Network (EURON), Project VISOR. ...
Acknowledgement This work has been partially granted by the Spanish Ministerio de Educación y Ciencia (MEC) and FEDER funds, Project n. ...
The model mechanism is validated in simulation and in a humanoid robot to perform a simple task, in which the robot imitates movements performed by a human demonstrator. ...
doi:10.5772/4821
fatcat:ybz3usowljectoogk2l7lwpww4
Adversarial Active Exploration for Inverse Dynamics Model Learning
[article]
2020
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2020; you can also visit the original URL.
The file type is application/pdf.
Other Versions
The latter is trained with samples collected by the former, and generates rewards for the former when it fails to predict the actual action taken by the former. ...
We evaluate the effectiveness of our method on several robotic arm and hand manipulation tasks against multiple baseline models. ...
Experimental Results In this section, we present experimental results for a series of robotic control tasks, and validate that (i) our method is effective for common robotic arm control and in-hand manipulation ...
arXiv:1806.10019v2
fatcat:pgliesgdu5f7pol3jswn66utoi
Active Inference in Robotics and Artificial Agents: Survey and Challenges
[article]
2021
arXiv
pre-print
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
Recently, it has been shown to be a promising approach to the problems of state-estimation and control under uncertainty, as well as a foundation for the construction of goal-driven behaviours in robotics ...
Active inference is a mathematical framework which originated in computational neuroscience as a theory of how the brain implements action, perception and learning. ...
ACKNOWLEDGMENT We would like to thank Karl Friston for his comments on the manuscript and his invaluable inspiration for AIF in robotics. ...
arXiv:2112.01871v1
fatcat:dux4iuejufb4bomn27eqv5rpea
Intelligent robot trends and predictions for the .net future
2001
Intelligent Robots and Computer Vision XX: Algorithms, Techniques, and Active Vision
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2017; you can also visit the original URL.
The file type is application/pdf.
In this type of learning, a critic provides a grade to the controller of an action module such as a robot. The adaptive critic is a good model for human learning. ...
An intelligent robot is a remarkably useful combination of a manipulator, sensors and controls. ...
In some modern simulation software, once a series of motions are selected, the robot code generator program can translate the motions into robot programming language automatically and download this program ...
doi:10.1117/12.444228
fatcat:xv65xlvamvb37n4566q6bueywy
Active Inferants: An Active Inference Framework for Ant Colony Behavior
2021
Frontiers in Behavioral Neuroscience
Preserved Fulltext
A copy of this work was available on the public web and has been preserved in the Wayback Machine. The capture dates from 2021; you can also visit the original URL.
The file type is application/pdf.
In this paper, we introduce an active inference model of ant colony foraging behavior, and implement the model in a series of in silico experiments. ...
Active inference is a multiscale approach to behavioral modeling that is being applied across settings in theoretical biology and ethology. ...
This is the scale that we explored here in this series of simulations. ...
doi:10.3389/fnbeh.2021.647732
pmid:34248515
pmcid:PMC8264549
fatcat:nvurzinpybc2hftnfah2atu4w4
« Previous
Showing results 1 — 15 out of 9,193 results