415 citations · 725 across the 47 of their papers we have counts for
9 papers · 1 filter
Hierarchical Policy Design for Sample-Efficient Learning of Robot Table Tennis Through Self-Play
Reza Mahjourian, Risto Miikkulainen, Nevena Lazic +2
Training robots with physical bodies requires developing new methods and action representations that allow the learning agents to explore the space of policies efficiently. This wo…
A Comparison of the Taguchi Method and Evolutionary Optimization in Multivariate Testing
Jingbo Jiang, Diego Legrand, Robert Severn +1
Multivariate testing has recently emerged as a promising technique in web interface design. In contrast to the standard A/B testing, multivariate approach aims at evaluating a larg…
Functional Generative Design: An Evolutionary Approach to 3D-Printing
Cem C. Tutum, Supawit Chockchowwat, Etienne Vouga +1
Consumer-grade printers are widely available, but their ability to print complex objects is limited. Therefore, new designs need to be discovered that serve the same function, but…
Evolutionary Architecture Search For Deep Multitask Networks
Jason Liang, Elliot Meyerson, Risto Miikkulainen
Multitask learning, i.e. learning several tasks at once with the same neural network, can improve performance in each of the tasks. Designing deep neural network architectures for…
From Nodes to Networks: Evolving Recurrent Neural Networks
Aditya Rawal, Risto Miikkulainen
Gated recurrent networks such as those composed of Long Short-Term Memory (LSTM) nodes have recently been used to improve state of the art in many sequential processing tasks such…
Pseudo-task Augmentation: From Deep Multitask Learning to Intratask Sharing---and Back
Elliot Meyerson, Risto Miikkulainen
Deep multitask learning boosts performance by sharing learned structure across related tasks. This paper adapts ideas from deep multitask learning to the setting where only a singl…
Enhanced Optimization with Composite Objectives and Novelty Selection
Hormoz Shahrzad, Daniel Fink, Risto Miikkulainen
An important benefit of multi-objective search is that it maintains a diverse population of candidates, which helps in deceptive problems in particular. Not all diversity is useful…
Enhancing Evolutionary Conversion Rate Optimization via Multi-armed Bandit Algorithms
Xin Qiu, Risto Miikkulainen
Conversion rate optimization means designing web interfaces such that more visitors perform a desired action (such as register or purchase) on the site. One promising approach, imp…
The Surprising Creativity of Digital Evolution: A Collection of Anecdotes from the Evolutionary Computation and Artificial Life Research Communities
Joel Lehman, Jeff Clune, Dusan Misevic +50
Biological evolution provides a creative fount of complex and subtle adaptations, often surprising the scientists who discover them. However, because evolution is an algorithmic pr…