About this Research Topic
One of the most prominent distinctions between machines and humans is the ability for cognitive behavior and learning. Traditionally, robotic machines were programmed to perform a specific function without the capability for adaptability or improvement. We now live in a world where robots are progressively integrated into our dynamic society, making it essential that robots and machines adapt to their ever-changing surroundings via machine learning.
This Research Topic aims to collate research that focuses on machine learning, improvement, and adaptability. We want to explore the ability of robots to perform tasks that require active cognition and interaction with their external environment.
This Research Topic welcomes research on but not limited to:
- Cognition (abstract thought, theory of mind, rational thinking, …)
- Robots and dynamic environments
- Reinforcement learning
- Transfer learning
- Solving tasks
- Calculation capability
This Research Topic aims to collate research that focuses on machine learning, improvement, and adaptability. We want to explore the ability of robots to perform tasks that require active cognition and interaction with their external environment.
This Research Topic welcomes research on but not limited to:
- Cognition (abstract thought, theory of mind, rational thinking, …)
- Robots and dynamic environments
- Reinforcement learning
- Transfer learning
- Solving tasks
- Calculation capability
Keywords: Machine Learning, calculation capability, adaptability, Reinforcement Learning
Important Note: All contributions to this Research Topic must be within the scope of the section and journal to which they are submitted, as defined in their mission statements. Frontiers reserves the right to guide an out-of-scope manuscript to a more suitable section or journal at any stage of peer review.
