Sentence examples for learning from demonstrations from inspiring English sources

The learning agent is typically called the learner while the observed agent is often an expert in popular applications such as in learning from demonstrations.

This paper addresses an important issue in learning from demonstrations that are provided by "naïve" human teachers people who do not have expertise in the machine learning algorithms used by the robot.

Two major challenges with Learning from Demonstration (LfD) are to identify what information in a demonstrated behavior requires attention by the robot, and to generalize the learned behavior such that the robot is able to perform the same behavior in novel situations.

Learning from demonstration has shown to be a suitable approach for learning control policies (CPs).

The performance of PSL as a method for learning from demonstration is evaluated with, and without, contextual information.

We present a comprehensive survey of robot Learning from Demonstration (LfD), a technique that develops policies from example state to action mappings.

This paper proposes a modular, behavior-based control architecture, which is particularly suited for "Learning from Demonstration" experiments in the spatial domain.

The core idea of acquiring skills by imitation has been labeled over the years with various names such as teaching by showing[14], robot coaching[15], programming by demonstration[16], or learning from demonstration (LfD) [17].

Reinforcement learning (RL) and learning from demonstration (LfD) are two popular families of algorithms for learning policies for sequential decision problems, but they are often ineffective in high-dimensional domains unless provided with either a great deal of problem-specific domain information or a carefully crafted representation of the state and dynamics of the world.

For example learning from demonstration can be used to teach a robot certain skills like simple manipulations of objects (Breazeal and Scassellati 2008; Schaal et al. 2003; Dillmann 2004).

In [14], behaviour primitives of the PHOENIX robot control architecture are incrementally learned from demonstrations.