AIMC Topic: Exploratory Behavior
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Analysis of behavioral flow resolves latent phenotypes.
Nature methods
Nov 12, 2024
The accurate detection and quantification of rodent behavior forms a cornerstone of basic biomedical research. Current data-driven approaches, which segment free exploratory behavior into clusters, suffer from low statistical power due to multiple te...
Automated analysis of a novel object recognition test in mice using image processing and machine learning.
Behavioural brain research
Sep 30, 2024
The novel object recognition test (NORT) is one of the most commonly employed behavioral tests in experimental animals designed to evaluate an animal's interest in and recognition of novelty. However, manual procedures, which rely on researchers' obs...
A transdisciplinary view on curiosity beyond linguistic humans: animals, infants, and artificial intelligence.
Biological reviews of the Cambridge Philosophical Society
Jan 29, 2024
Curiosity is a core driver for life-long learning, problem-solving and decision-making. In a broad sense, curiosity is defined as the intrinsically motivated acquisition of novel information. Despite a decades-long history of curiosity research and t...
Preschoolers search longer when there is more information to be gained.
Developmental science
May 21, 2023
What drives children to explore and learn when external rewards are uncertain or absent? Across three studies, we tested whether information gain itself acts as an internal reward and suffices to motivate children's actions. We measured 24-56-month-o...
Automated Anomaly Detection via Curiosity-Guided Search and Self-Imitation Learning.
IEEE transactions on neural networks and learning systems
Jun 1, 2022
Anomaly detection is an important data mining task with numerous applications, such as intrusion detection, credit card fraud detection, and video surveillance. However, given a specific complicated task with complicated data, the process of building...
End-to-End Autonomous Exploration with Deep Reinforcement Learning and Intrinsic Motivation.
Computational intelligence and neuroscience
Dec 16, 2021
Developing artificial intelligence (AI) agents is challenging for efficient exploration in visually rich and complex environments. In this study, we formulate the exploration question as a reinforcement learning problem and rely on intrinsic motivati...
Haptic Exploration During Fast Video Playback: Vibrotactile Support for Event Search in Robot Operation Videos.
IEEE transactions on haptics
Dec 10, 2019
Fast playback allows quick video exploration, but it also decreases the saliency of short events. We propose a haptic exploration for detection of short events during fast video playback, considering that event-related information in vibrotactile fee...
Haptic Material Analysis and Classification Inspired by Human Exploratory Procedures.
IEEE transactions on haptics
Nov 8, 2019
We present a framework for the acquisition and parametrization of object material properties. The introduced acquisition device, denoted as Texplorer2, is able to extract surface material properties while a human operator is performing exploratory pr...
Developmental Approach for Behavior Learning Using Primitive Motion Skills.
International journal of neural systems
Aug 6, 2017
Imitation learning through self-exploration is essential in developing sensorimotor skills. Most developmental theories emphasize that social interactions, especially understanding of observed actions, could be first achieved through imitation, yet t...
What do we learn about development from baby robots?
Wiley interdisciplinary reviews. Cognitive science
Dec 1, 2016
Understanding infant development is one of the great scientific challenges of contemporary science. In addressing this challenge, robots have proven useful as they allow experimenters to model the developing brain and body and understand the processe...
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