415 citations · 725 across the 47 of their papers we have counts for
31 papers · 1 filter
GPU-Accelerated Rule Evaluation and Evolution
Hormoz Shahrzad, Risto Miikkulainen
This paper introduces an innovative approach to boost the efficiency and scalability of Evolutionary Rule-based machine Learning (ERL), a key technique in explainable AI. While tra…
Asynchronous Evolution of Deep Neural Network Architectures
Jason Liang, Hormoz Shahrzad, Risto Miikkulainen
Many evolutionary algorithms (EAs) take advantage of parallel evaluation of candidates. However, if evaluation times vary significantly, many worker nodes (i.e.,\ compute clients)…
Evolving Strategies for Competitive Multi-Agent Search
Erkin Bahceci, Riitta Katila, Risto Miikkulainen
While evolutionary computation is well suited for automatic discovery in engineering, it can also be used to gain insight into how humans and organizations could perform more effec…
Accelerating Evolution Through Gene Masking and Distributed Search
Hormoz Shahrzad, Risto Miikkulainen
In building practical applications of evolutionary computation (EC), two optimizations are essential. First, the parameters of the search method need to be tuned to the domain in o…
Shortest Edit Path Crossover: A Theory-driven Solution to the Permutation Problem in Evolutionary Neural Architecture Search
Xin Qiu, Risto Miikkulainen
Population-based search has recently emerged as a possible alternative to Reinforcement Learning (RL) for black-box neural architecture search (NAS). It performs well in practice e…
Effective Mutation Rate Adaptation through Group Elite Selection
Akarsh Kumar, Bo Liu, Risto Miikkulainen +1
Evolutionary algorithms are sensitive to the mutation rate (MR); no single value of this parameter works well across domains. Self-adaptive MR approaches have been proposed but the…
DIAS: A Domain-Independent Alife-Based Problem-Solving System
Babak Hodjat, Hormoz Shahrzad, Risto Miikkulainen
A domain-independent problem-solving system based on principles of Artificial Life is introduced. In this system, DIAS, the input and output dimensions of the domain are laid out i…
Simple Genetic Operators are Universal Approximators of Probability Distributions (and other Advantages of Expressive Encodings)
Elliot Meyerson, Xin Qiu, Risto Miikkulainen
This paper characterizes the inherent power of evolutionary algorithms. This power depends on the computational properties of the genetic encoding. With some encodings, two parents…
Evolving GAN Formulations for Higher Quality Image Synthesis
Santiago Gonzalez, Mohak Kant, Risto Miikkulainen
Generative Adversarial Networks (GANs) have extended deep learning to complex generation and translation tasks across different data modalities. However, GANs are notoriously diffi…
The Traveling Observer Model: Multi-task Learning Through Spatial Variable Embeddings
Elliot Meyerson, Risto Miikkulainen
This paper frames a general prediction system as an observer traveling around a continuous space, measuring values at some locations, and predicting them at others. The observer is…
Creative AI Through Evolutionary Computation: Principles and Examples
Risto Miikkulainen
The main power of artificial intelligence is not in modeling what we already know, but in creating solutions that are new. Such solutions exist in extremely large, high-dimensional…
Generalization of Agent Behavior through Explicit Representation of Context
Cem C Tutum, Suhaib Abdulquddos, Risto Miikkulainen
In order to deploy autonomous agents in digital interactive environments, they must be able to act robustly in unseen situations. The standard machine learning approach is to inclu…
From Prediction to Prescription: Evolutionary Optimization of Non-Pharmaceutical Interventions in the COVID-19 Pandemic
Risto Miikkulainen, Olivier Francon, Elliot Meyerson +3
Several models have been developed to predict how the COVID-19 pandemic spreads, and how it could be contained with non-pharmaceutical interventions (NPIs) such as social distancin…
Adapting to Unseen Environments through Explicit Representation of Context
Cem C. Tutum, Risto Miikkulainen
In order to deploy autonomous agents to domains such as autonomous driving, infrastructure management, health care, and finance, they must be able to adapt safely to unseen situati…
Effective Reinforcement Learning through Evolutionary Surrogate-Assisted Prescription
Olivier Francon, Santiago Gonzalez, Babak Hodjat +4
There is now significant historical data available on decision making in organizations, consisting of the decision problem, what decisions were made, and how desirable the outcomes…
Regularized Evolutionary Population-Based Training
Jason Liang, Santiago Gonzalez, Hormoz Shahrzad +1
Metalearning of deep neural network (DNN) architectures and hyperparameters has become an increasingly important area of research. At the same time, network regularization has been…
Enhanced Optimization with Composite Objectives and Novelty Pulsation
Hormoz Shahrzad, Babak Hodjat, Camille Dollé +5
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…
Functional Generative Design of Mechanisms with Recurrent Neural Networks and Novelty Search
Cameron R. Wolfe, Cem C. Tutum, Risto Miikkulainen
Consumer-grade 3D printers have made it easier to fabricate aesthetic objects and static assemblies, opening the door to automated design of such objects. However, while static des…
Evolutionary Neural AutoML for Deep Learning
Jason Liang, Elliot Meyerson, Babak Hodjat +3
Deep neural networks (DNNs) have produced state-of-the-art results in many benchmarks and problem domains. However, the success of DNNs depends on the proper configuration of its a…
Creative AI Through Evolutionary Computation
Risto Miikkulainen
The main power of artificial intelligence is not in modeling what we already know, but in creating solutions that are new. Such solutions exist in extremely large, high-dimensional…
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…