A systematic review on reinforcement learning-based robotics within the last decade
Robotics is one of the many tools that is making a substantial difference as the world is
experiencing the fourth industrial revolution. To ease control over this engineering marvel …
experiencing the fourth industrial revolution. To ease control over this engineering marvel …
Hierarchical control over effortful behavior by rodent medial frontal cortex: A computational model.
CB Holroyd, SM McClure - Psychological review, 2015 - psycnet.apa.org
The anterior cingulate cortex (ACC) has been the focus of intense research interest in recent
years. Although separate theories relate ACC function variously to conflict monitoring …
years. Although separate theories relate ACC function variously to conflict monitoring …
Strong and weak alignment of large language models with human values
Minimizing negative impacts of Artificial Intelligent (AI) systems on human societies without
human supervision requires them to be able to align with human values. However, most …
human supervision requires them to be able to align with human values. However, most …
Toward self-aware robots
Despite major progress in Robotics and AI, robots are still basically “zombies” repeatedly
achieving actions and tasks without understanding what they are doing. Deep-Learning AI …
achieving actions and tasks without understanding what they are doing. Deep-Learning AI …
Review of neurobiologically based mobile robot navigation system research performed since 2000
In an attempt to better understand how the navigation part of the brain works and to possibly
create smarter and more reliable navigation systems, many papers have been written in the …
create smarter and more reliable navigation systems, many papers have been written in the …
Modeling choice and reaction time during arbitrary visuomotor learning through the coordination of adaptive working memory and reinforcement learning
Current learning theory provides a comprehensive description of how humans and other
animals learn, and places behavioral flexibility and automaticity at heart of adaptive …
animals learn, and places behavioral flexibility and automaticity at heart of adaptive …
Reducing computational cost during robot navigation and human–robot interaction with a human-inspired reinforcement learning architecture
We present a new neuro-inspired reinforcement learning architecture for robot online
learning and decision-making during both social and non-social scenarios. The goal is to …
learning and decision-making during both social and non-social scenarios. The goal is to …
Robot fast adaptation to changes in human engagement during simulated dynamic social interaction with active exploration in parameterized reinforcement learning
Dynamic uncontrolled human-robot interactions (HRIs) require robots to be able to adapt to
changes in the human's behavior and intentions. Among relevant signals, nonverbal cues …
changes in the human's behavior and intentions. Among relevant signals, nonverbal cues …
Active exploration and parameterized reinforcement learning applied to a simulated human-robot interaction task
Online model-free reinforcement learning (RL) methods with continuous actions are playing
a prominent role when dealing with real-world applications such as Robotics. However …
a prominent role when dealing with real-world applications such as Robotics. However …
Goal-oriented robot navigation learning using a multi-scale space representation
M Llofriu, G Tejera, M Contreras, T Pelc, JM Fellous… - Neural Networks, 2015 - Elsevier
There has been extensive research in recent years on the multi-scale nature of hippocampal
place cells and entorhinal grid cells encoding which led to many speculations on their role in …
place cells and entorhinal grid cells encoding which led to many speculations on their role in …