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07/17/2023
Towards Self-Assembling Artificial Neural Networks through Neural Developmental Programs
Biological nervous systems are created in a fundamentally different way ...
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07/07/2023
CLIPMasterPrints: Fooling Contrastive Language-Image Pre-training Using Latent Variable Evolution
Models leveraging both visual and textual data such as Contrastive Langu...
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05/25/2023
Learning to Act through Evolution of Neural Diversity in Random Neural Networks
Biological nervous systems consist of networks of diverse, sophisticated...
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02/12/2023
MarioGPT: Open-Ended Text2Level Generation through Large Language Models
Procedural Content Generation (PCG) algorithms provide a technique to ge...
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01/31/2023
Skill Decision Transformer
Recent work has shown that Large Language Models (LLMs) can be incredibl...
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06/14/2022
Severe Damage Recovery in Evolving Soft Robots through Differentiable Programming
Biological systems are very robust to morphological damage, but artifici...
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05/31/2022
Mario Plays on a Manifold: Generating Functional Content in Latent Space through Differential Geometry
Deep generative models can automatically create content of diverse types...
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05/12/2022
Minimal Neural Network Models for Permutation Invariant Agents
Organisms in nature have evolved to exhibit flexibility in face of chang...
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04/25/2022
Goal-Guided Neural Cellular Automata: Learning to Control Self-Organising Systems
Inspired by cellular growth and self-organization, Neural Cellular Autom...
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04/25/2022
HyperNCA: Growing Developmental Networks with Neural Cellular Automata
In contrast to deep reinforcement learning agents, biological neural net...
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03/22/2022
A Unified Substrate for Body-Brain Co-evolution
The discovery of complex multicellular organism development took million...
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03/14/2022
Physical Neural Cellular Automata for 2D Shape Classification
Materials with the ability to self-classify their own shape have the pot...
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01/28/2022
Variational Neural Cellular Automata
In nature, the process of cellular growth and differentiation has lead t...
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07/14/2021
Safer Reinforcement Learning through Transferable Instinct Networks
Random exploration is one of the main mechanisms through which reinforce...
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07/05/2021
Dealing with Adversarial Player Strategies in the Neural Network Game iNNk through Ensemble Learning
Applying neural network (NN) methods in games can lead to various new an...
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05/27/2021
Hybrid Encoding For Generating Large Scale Game Level Patterns With Local Variations Using a GAN
Generative Adversarial Networks (GANs) are a powerful indirect genotype-...
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05/18/2021
Fast Game Content Adaptation Through Bayesian-based Player Modelling
In games, as well as many user-facing systems, adapting content to users...
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04/16/2021
Evolving and Merging Hebbian Learning Rules: Increasing Generalization by Decreasing the Number of Rules
Generalization to out-of-distribution (OOD) circumstances after training...
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03/29/2021
Rapid Risk Minimization with Bayesian Models Through Deep Learning Approximation
In this paper, we introduce a novel combination of Bayesian Models (BMs)...
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03/15/2021
Growing 3D Artefacts and Functional Machines with Neural Cellular Automata
Neural Cellular Automata (NCAs) have been proven effective in simulating...
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02/12/2021
Improving Object Detection in Art Images Using Only Style Transfer
Despite recent advances in object detection using deep learning neural n...
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02/04/2021
Regenerating Soft Robots through Neural Cellular Automata
Morphological regeneration is an important feature that highlights the e...
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01/15/2021
Player-AI Interaction: What Neural Network Games Reveal About AI as Play
The advent of artificial intelligence (AI) and machine learning (ML) bri...
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12/08/2020
EvoCraft: A New Challenge for Open-Endedness
This paper introduces EvoCraft, a framework for Minecraft designed to st...
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11/23/2020
Evolutionary Planning in Latent Space
Planning is a powerful approach to reinforcement learning with several d...
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11/13/2020
Testing the Genomic Bottleneck Hypothesis in Hebbian Meta-Learning
Recent work has shown promising results using Hebbian meta-learning to s...
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10/15/2020
The power of pictures: using ML assisted image generation to engage the crowd in complex socioscientific problems
Human-computer image generation using Generative Adversarial Networks (G...
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10/09/2020
Deep Learning for Procedural Content Generation
Procedural content generation in video games has a long history. Existin...
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09/18/2020
AI and Wargaming
Recent progress in Game AI has demonstrated that given enough data from ...
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08/13/2020
crea.blender: A Neural Network-Based Image Generation Game to Assess Creativity
We present a pilot study on crea.blender, a novel co-creative game desig...
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07/17/2020
iNNk: A Multi-Player Game to Deceive a Neural Network
This paper presents iNNK, a multiplayer drawing game where human players...
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07/06/2020
Meta-Learning through Hebbian Plasticity in Random Networks
Lifelong learning and adaptability are two defining aspects of biologica...
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05/26/2020
Capturing Local and Global Patterns in Procedural Content Generation via Machine Learning
Recent procedural content generation via machine learning (PCGML) method...
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05/15/2020
Finding Game Levels with the Right Difficulty in a Few Trials through Intelligent Trial-and-Error
Methods for dynamic difficulty adjustment allow games to be tailored to ...
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05/06/2020
Safe Reinforcement Learning through Meta-learned Instincts
An important goal in reinforcement learning is to create agents that can...
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04/03/2020
CPPN2GAN: Combining Compositional Pattern Producing Networks and GANs for Large-scale Pattern Generation
Generative Adversarial Networks (GANs) are proving to be a powerful indi...
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03/31/2020
Interactive Evolution and Exploration Within Latent Level-Design Space of Generative Adversarial Networks
Generative Adversarial Networks (GANs) are an emerging form of indirect ...
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02/24/2020
From Chess and Atari to StarCraft and Beyond: How Game AI is Driving the World of AI
This paper reviews the field of Game AI, which not only deals with creat...
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01/07/2020
Revealing Neural Network Bias to Non-Experts Through Interactive Counterfactual Examples
AI algorithms are not immune to biases. Traditionally, non-experts have ...
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12/29/2019
Improving Deep Neuroevolution via Deep Innovation Protection
Evolutionary-based optimization approaches have recently shown promising...
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11/29/2019
Procedural Content Generation: From Automatically Generating Game Levels to Increasing Generality in Machine Learning
The idea behind procedural content generation (PCG) in games is to creat...
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10/03/2019
Bootstrapping Conditional GANs for Video Game Level Generation
Generative Adversarial Networks (GANs) have shown im-pressive results fo...
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07/30/2019
An artifcial life approach to studying niche differentiation in soundscape ecology
Artificial life simulations are an important tool in the study of ecolog...
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07/05/2019
Learning a Behavioral Repertoire from Demonstrations
Imitation Learning (IL) is a machine learning approach to learn a policy...
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04/28/2019
Deep Neuroevolution of Recurrent and Discrete World Models
Neural architectures inspired by our own human cognitive system, such as...
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06/28/2018
Procedural Level Generation Improves Generality of Deep Reinforcement Learning
Over the last few years, deep reinforcement learning (RL) has shown impr...
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05/02/2018
Evolving Mario Levels in the Latent Space of a Deep Convolutional Generative Adversarial Network
Generative Adversarial Networks (GANs) are a machine learning approach c...
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04/18/2018
A Robot to Shape your Natural Plant: The Machine Learning Approach to Model and Control Bio-Hybrid Systems
Bio-hybrid systems---close couplings of natural organisms with technolog...
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03/19/2018
Automated Curriculum Learning by Rewarding Temporally Rare Events
Reward shaping allows reinforcement learning (RL) agents to accelerate l...
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01/24/2018
