Search Results for author:
Found 12 papers, 5 papers with code
Hearing the shape of an arena with spectral swarm robotics
Diffusion over a domain is mathematically encapsulated by the Laplacian, a linear operator that measures the local curvature of a function.
Joint Intrinsic Motivation for Coordinated Exploration in Multi-Agent Deep Reinforcement Learning
We demonstrate the strengths of this approach both in a synthetic environment designed to reveal shortcomings of state-of-the-art MADRL methods, and in simulated robotic tasks.
Meta-control of social learning strategies
Based on these findings, we hypothesized that meta-control of individual and social learning strategies provides effective and sample-efficient learning in volatile and uncertain environments.
Policy Search with Rare Significant Events: Choosing the Right Partner to Cooperate with
This paper focuses on a class of reinforcement learning problems where significant events are rare and limited to a single positive reward per episode.
DREAM Architecture: a Developmental Approach to Open-Ended Learning in Robotics
Robots are still limited to controlled conditions, that the robot designer knows with enough details to endow the robot with the appropriate models or behaviors.
Online Trajectory Planning Through Combined Trajectory Optimization and Function Approximation: Application to the Exoskeleton Atalante
Autonomous robots require online trajectory planning capability to operate in the real world.
Exploring Self-Assembling Behaviors in a Swarm of Bio-micro-robots using Surrogate-Assisted MAP-Elites
Swarms of molecular robots are a promising approach to create specific shapes at the microscopic scale through self-assembly.
Automatic Calibration of Artificial Neural Networks for Zebrafish Collective Behaviours using a Quality Diversity Algorithm
During the last two decades, various models have been proposed for fish collective motion.
Evolutionary optimisation of neural network models for fish collective behaviours in mixed groups of robots and zebrafish
These models are designed to be implementable as robot controllers to form mixed-groups of fish and robots, using few a priori knowledge of the fish behaviours.
How to Blend a Robot within a Group of Zebrafish: Achieving Social Acceptance through Real-time Calibration of a Multi-level Behavioural Model
The calibrated model is updated on the robot and tested during the experiments.
Embodied Evolution in Collective Robotics: A Review
This paper provides an overview of evolutionary robotics techniques applied to on-line distributed evolution for robot collectives -- namely, embodied evolution.
