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Found 8 papers, 0 papers with code
Non-verbal information in spontaneous speech -- towards a new framework of analysis
Non-verbal signals in speech are encoded by prosody and carry information that ranges from conversation action to attitude and emotion.
Fidelity and Consistency in Iterative Probabilistic Set Replication: Comparing Bi-Parental and Mono-Parental Methods
We first sample a cohort of several such sets around an initial code, and probabilistically replicate each set once, creating a new same-size cohort, which we then subject to the same process.
The Human-or-Machine Matter: Turing-Inspired Reflections on an Everyday Issue
In his seminal paper ``Computing Machinery and Intelligence'', Alan Turing introduced the ``imitation game'' as part of exploring the concept of machine intelligence.
Constrained Reinforcement Learning for Robotics via Scenario-Based Programming
Deep reinforcement learning (DRL) has achieved groundbreaking successes in a wide variety of robotic applications.
Verifying Learning-Based Robotic Navigation Systems
Our work is the first to establish the usefulness of DNN verification in identifying and filtering out suboptimal DRL policies in real-world robots, and we believe that the methods presented here are applicable to a wide range of systems that incorporate deep-learning-based agents.
Scenario-Assisted Deep Reinforcement Learning
In this work-in-progress report, we propose a technique for enhancing the reinforcement learning training process (specifically, its reward calculation), in a way that allows human engineers to directly contribute their expert knowledge, making the agent under training more likely to comply with various relevant constraints.
Expecting the Unexpected: Developing Autonomous-System Design Principles for Reacting to Unpredicted Events and Conditions
When developing autonomous systems, engineers and other stakeholders make great effort to prepare the system for all foreseeable events and conditions.
