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Learning system dynamics via deep recurrent and conditional neural systems
(IEEE, 2021)
Although there are various mathematical methods for modeling system dynamics, more general solutions can be achieved using deep learning based on data. Alternative deep learning methods are presented in parallel with the ...
Trust me! I am a robot: an affective computational account of scaffolding in robot-robot interaction
(IEEE, 2021-08-08)
Forming trust in a biological or artificial interaction partner that provides reliable strategies and employing the learned strategies to scaffold another agent are critical problems that are often addressed separately in ...
Effect regulated projection of robot’s action space for production and prediction of manipulation primitives through learning progress and predictability based exploration
(IEEE, 2021-06)
In this study, we propose an effective action parameter exploration mechanism that enables efficient discovery of robot actions through interacting with objects in a simulated table-top environment. For this, the robot ...
Inferring cost functions using reward parameter search and policy gradient reinforcement learning
(IEEE, 2021)
This study focuses on inferring cost functions of obtained movement data using reward parameter search and policy gradient based Reinforcement Learning (RL). The behavior data for this task is obtained through a series of ...
Guest editorial special issue on continual unsupervised sensorimotor learning
(IEEE, 2021-06)
The pursuit of higher levels of autonomy and versatility in robotics is arguably led by two main factors. First, as we push robots out of the labs and production lines, it becomes increasingly challenging to design for all ...
Learning medical suturing primitives for autonomous suturing
(IEEE, 2021)
This paper focuses on a learning from demonstration approach for autonomous medical suturing. A conditional neural network is used to learn and generate suturing primitives trajectories which were conditioned on desired ...
An ecologically valid reference frame for perspective invariant action recognition
(IEEE, 2021)
In robotics, objects and body parts can be represented in various coordinate frames to ease computation. In biological systems, body or body part centered coordinate frames have been proposed as possible reference frames ...
Modeling robot trust based on emergent emotion in an interactive task
(IEEE, 2021)
Trust is an essential component in human-human and human-robot interactions. The factors that play potent roles in these interactions have been an attractive issue in robotics. However, the studies that aim at developing ...
Combined weight and density bounds on the polynomial threshold function representation of Boolean functions
(Elsevier, 2022-08)
In an earlier report it was shown that an arbitrary n-variable Boolean function f can be represented as a polynomial threshold function (PTF) with 0.75×2n or less number of monomials. In this report, we derive an upper ...
Multimodal reinforcement learning for partner specific adaptation in robot-multi-robot interaction
(IEEE, 2022)
Successful and efficient teamwork requires knowledge of the individual team members' expertise. Such knowledge is typically acquired in social interaction and forms the basis for socially intelligent, partner-Adapted ...
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