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Implementation of a Neural Natural Language Understanding Component for Arabic Dialogue Systems
Natural Language Understanding (NLU) is considered a core component in implementing dialogue systems. NLU has been greatly enhanced by …
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Real-time Motion Planning in Changing Environments Using Topology-based Encoding of Past Knowledge
Trajectory planning and replanning in complex environments often reuses very little information from the previous solutions. This is …
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Accelerating Model Learning with Inter-robot Knowledge Transfer
Online learning of a robot’s inverse dynamics model for trajectory tracking necessitates an interaction between the robot and its …
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Hierarchical Subtask Discovery with Non-negative Matrix Factorization
Hierarchical reinforcement learning methods offer a powerful means of planning flexible behavior in complicated domains. However, …
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Social Cobots: Anticipatory Decision-Making for Collaborative Robots Incorporating Unexpected Human Behaviors
We propose an architecture as a robot’s decision-making mechanism to anticipate a human’s state of mind, and so plan …
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Belief Reward Shaping in Reinforcement Learning
A key challenge in many reinforcement learning problems is delayed rewards, which can significantly slow down learning. Although reward …
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Raw Material Selection for Object Construction
An important step in the construction of novel objects is the ability to recognise combinations of raw materials which are likely to be …
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Tracking Influence between Naïve Bayes Models using Score-Based Structure Learning
Current structure learning practices in Bayesian networks have been developed to learn the structure between observable variables and …
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Fingerprint Minutiae Extraction using Deep Learning
The high variability of fingerprint data (owing to, e.g., differences in quality, moisture conditions, and scanners) makes the task of …
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Online Constrained Model-based Reinforcement Learning
Applying reinforcement learning to robotic systems poses a number of challenging problems. A key requirement is the ability to handle …
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