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Found 8 papers, 0 papers with code
Correspondence learning between morphologically different robots via task demonstrations
To be specific, besides robots with similar morphologies with different degrees of freedom, we show that a fixed-based manipulator robot with joint control and a differential drive mobile robot can be addressed within the proposed framework.
High-level Features for Resource Economy and Fast Learning in Skill Transfer
To be concrete, in our simulation experiments, we either apply principal component analysis (PCA) or slow feature analysis (SFA) on the signals collected from the last hidden layer of a deep network while it performs a source task, and use these features for skill transfer in a new target task.
On the weight and density bounds of polynomial threshold functions
In this report, we show that all n-variable Boolean function can be represented as polynomial threshold functions (PTF) with at most $0. 75 \times 2^n$ non-zero integer coefficients and give an upper bound on the absolute value of these coefficients.
Situated GAIL: Multitask imitation using task-conditioned adversarial inverse reinforcement learning
This study proposes an extended framework called situated GAIL (S-GAIL), in which a task variable is introduced to both the discriminator and generator of the GAIL framework.
Compensated Integrated Gradients to Reliably Interpret EEG Classification
Integrated gradients are widely employed to evaluate the contribution of input features in classification models because it satisfies the axioms for attribution of prediction.
On- and Off-Policy Monotonic Policy Improvement
Monotonic policy improvement and off-policy learning are two main desirable properties for reinforcement learning algorithms.
Where do goals come from? A Generic Approach to Autonomous Goal-System Development
Goals express agents' intentions and allow them to organize their behavior based on low-dimensional abstractions of high-dimensional world states.
Real-time face swapping as a tool for understanding infant self-recognition
To study the preference of infants for contingency of movements and familiarity of faces during self-recognition task, we built, as an accurate and instantaneous imitator, a real-time face- swapper for videos.
