Paper Info
Title
Humanoid Cognitive Robots That Learn by Imitating: Implications for Consciousness Studies.
Abstract
While the concept of a conscious machine is intriguing, producing such a machine remains controversial and challenging. Here, we describe how our work on creating a humanoid cognitive robot that learns to perform tasks via imitation learning relates to this issue. Our discussion is divided into three parts. First, we summarize our previous framework for advancing the understanding of the nature of phenomenal consciousness. This framework is based on identifying computational correlates of consciousness. Second, we describe a cognitive robotic system that we recently developed that learns to perform tasks by imitating human-provided demonstrations. This humanoid robot uses cause effect reasoning to infer a demonstrator's intentions in performing a task, rather than just imitating the observed actions verbatim. In particular, its cognitive components center on top-down control of a working memory that retains the explanatory interpretations that the robot constructs during learning. Finally, we describe our ongoing work that is focused on converting our robot's imitation learning cognitive system into purely neurocomputational form, including both its low-level cognitive neuromotor components, its use of working memory, and its causal reasoning mechanisms. Based on our initial results, we argue that the top-down cognitive control of working memory, and in particular its gating mechanisms, is an important potential computational correlate of consciousness in humanoid robots. We conclude that developing high-level neuro-cognitive control systems for cognitive robots and using them to search for computational correlates of consciousness provides an important approach to advancing our understanding of consciousness, and that it provides a credible and achievable route to ultimately developing a phenomenally conscious machine.
Year
DOI
Venue
2018
10.3389/frobt.2018.00001
FRONTIERS IN ROBOTICS AND AI
Keywords
Field
DocType
machine consciousness,artificial consciousness,neural network gating mechanisms,cognitive robots,cognitive phenomenology,imitation learning,computational explanatory gap,working memory
Artificial consciousness,Causal reasoning,Computer science,Cognitive science,Working memory,Consciousness,Artificial intelligence,Cognition,Robot,Neurocognitive,Machine learning,Humanoid robot
Journal
Volume
ISSN
Citations 
5.0
2296-9144
1
PageRank 
References 
Authors
0.36
11
3
Name
Order
Citations
PageRank
James A. Reggia11000276.13
Garrett E Katz2124.32
Gregory P. Davis311.04