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Found 8 papers, 2 papers with code
Self-Reproduction and Evolution in Cellular Automata: 25 Years after Evoloops
The year of 2024 marks the 25th anniversary of the publication of evoloops, an evolutionary variant of Chris Langton's self-reproducing loops which proved that Darwinian evolution of self-reproducing organisms by variation and natural selection is possible within deterministic cellular automata.
How Do Human Users Teach a Continual Learning Robot in Repeated Interactions?
Continual learning (CL) has emerged as an important avenue of research in recent years, at the intersection of Machine Learning (ML) and Human-Robot Interaction (HRI), to allow robots to continually learn in their environments over long-term interactions with humans.
A Personalized Household Assistive Robot that Learns and Creates New Breakfast Options through Human-Robot Interaction
In this paper, we present a cognitive architecture for a household assistive robot that can learn personalized breakfast options from its users and then use the learned knowledge to set up a table for breakfast.
Continual Learning through Human-Robot Interaction -- Human Perceptions of a Continual Learning Robot in Repeated Interactions
Our results suggest that participants' perceptions of trust, competence, and usability of a continual learning robot significantly decrease over multiple sessions if the robot forgets previously learned objects.
Don't Forget to Buy Milk: Contextually Aware Grocery Reminder Household Robot
The robot can also use the learned knowledge to correctly predict missing items over multiple weeks and it is robust against sensory and perceptual errors.
Measuring Time with Minimal Clocks
Clock cascades show a "condensation effect" and the composite clock shows various regimes of markedly different dynamics.
Robots Learning to Say `No': Prohibition and Rejective Mechanisms in Acquisition of Linguistic Negation
`No' belongs to the first ten words used by children and embodies the first active form of linguistic negation.
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Computational Understanding and Manipulation of Symmetries
For natural and artificial systems with some symmetry structure, computational understanding and manipulation can be achieved without learning by exploiting the algebraic structure.
