HyperNCA: Growing Developmental Networks with Neural Cellular Automata

In contrast to deep reinforcement learning agents, biological neural networks are grown through a self-organized developmental process. Here we propose a new hypernetwork approach to grow artificial neural networks based on neural cellular automata (NCA). Inspired by self-organising systems and information-theoretic approaches to developmental biology, we show that our HyperNCA method can grow neural networks capable of solving common reinforcement learning tasks. Finally, we explore how the same approach can be used to build developmental metamorphosis networks capable of transforming their weights to solve variations of the initial RL task.Comment: Paper accepted as a conference paper at ICLR 'From Cells to Societies' workshop 202

EvoCraft: A New Challenge for Open-Endedness

This paper introduces EvoCraft, a framework for Minecraft designed to study open-ended algorithms. We introduce an API that provides an open-source Python interface for communicating with Minecraft to place and track blocks. In contrast to previous work in Minecraft that focused on learning to play the game, the grand challenge we pose here is to automatically search for increasingly complex artifacts in an open-ended fashion. Compared to other environments used to study open-endedness, Minecraft allows the construction of almost any kind of structure, including actuated machines with circuits and mechanical components. We present initial baseline results in evolving simple Minecraft creations through both interactive and automated evolution. While evolution succeeds when tasked to grow a structure towards a specific target, it is unable to find a solution when rewarded for creating a simple machine that moves. Thus, EvoCraft offers a challenging new environment for automated search methods (such as evolution) to find complex artifacts that we hope will spur the development of more open-ended algorithms. A Python implementation of the EvoCraft framework is available at: https://github.com/real-itu/Evocraft-py

MarioGPT: Open-Ended Text2Level Generation through Large Language Models

Procedural Content Generation (PCG) algorithms provide a technique to generate complex and diverse environments in an automated way. However, while generating content with PCG methods is often straightforward, generating meaningful content that reflects specific intentions and constraints remains challenging. Furthermore, many PCG algorithms lack the ability to generate content in an open-ended manner. Recently, Large Language Models (LLMs) have shown to be incredibly effective in many diverse domains. These trained LLMs can be fine-tuned, re-using information and accelerating training for new tasks. In this work, we introduce MarioGPT, a fine-tuned GPT2 model trained to generate tile-based game levels, in our case Super Mario Bros levels. We show that MarioGPT can not only generate diverse levels, but can be text-prompted for controllable level generation, addressing one of the key challenges of current PCG techniques. As far as we know, MarioGPT is the first text-to-level model. We also combine MarioGPT with novelty search, enabling it to generate diverse levels with varying play-style dynamics (i.e. player paths). This combination allows for the open-ended generation of an increasingly diverse range of content

Growing 3D Artefacts and Functional Machines with Neural Cellular Automata

Neural Cellular Automata (NCAs) have been proven effective in simulating morphogenetic processes, the continuous construction of complex structures from very few starting cells. Recent developments in NCAs lie in the 2D domain, namely reconstructing target images from a single pixel or infinitely growing 2D textures. In this work, we propose an extension of NCAs to 3D, utilizing 3D convolutions in the proposed neural network architecture. Minecraft is selected as the environment for our automaton since it allows the generation of both static structures and moving machines. We show that despite their simplicity, NCAs are capable of growing complex entities such as castles, apartment blocks, and trees, some of which are composed of over 3,000 blocks. Additionally, when trained for regeneration, the system is able to regrow parts of simple functional machines, significantly expanding the capabilities of simulated morphogenetic systems. The code for the experiment in this paper can be found at: https://github.com/real-itu/3d-artefacts-nca

Differentiable Logic Machines

The integration of reasoning, learning, and decision-making is key to build more general AI systems. As a step in this direction, we propose a novel neural-logic architecture that can solve both inductive logic programming (ILP) and deep reinforcement learning (RL) problems. Our architecture defines a restricted but expressive continuous space of first-order logic programs by assigning weights to predicates instead of rules. Therefore, it is fully differentiable and can be efficiently trained with gradient descent. Besides, in the deep RL setting with actor-critic algorithms, we propose a novel efficient critic architecture. Compared to state-of-the-art methods on both ILP and RL problems, our proposition achieves excellent performance, while being able to provide a fully interpretable solution and scaling much better, especially during the testing phase

Périodes du groupe fondamental motivique de la droite projective moins zero, l’infini et les racines n-èmes de l’unité

Following F. Brown's point of view, we look at the Hopf algebra structure of motivic cyclotomic multiple zeta values, which are motivic periods of the fundamental groupoid of the projective line minus 0, infinity and N roots of unity. By application of a surjective period map (conjectured isomorphism), we deduce results (generating families, identities, etc.) on cyclotomic multiple zeta values, which are complex numbers. The coaction of this Hopf algebra (explicit combinatorial formula) is the dual of the action of a so-called motivic Galois group on these specific motivic periods. This entire study was motivated by the hope of a Galois theory for periods, which should extend the usual one for algebraic numbers.(i)In the first part, we focus on the case of motivic multiple zeta values (N = 1) and Euler sums (N = 2). In particular, we present new bases for motivic multiple zeta values: one via motivic Euler sums, and another (depending on an analytic conjecture) which is known as the Hoffman star basis; under a general motivic identity that we conjecture, these bases are identical. (ii)In the second part, we apply some Galois descents ideas to the study of these periods, and examine how multiple zeta values relative to N' roots of unity are embedded into those relative to N roots, when N' divide N. After giving some general criteria for any N, we focus on the cases N=2,3,4, 6, 8, for which the motivic fundamental group generates the category of mixed Tate motives on the ring of integer of the N cyclotomic field ramified in N (unramified if N=6). For those N, we are able to construct Galois descents explicitly, and extend P. Deligne's results.En s'inspirant du point de vue adopté par Francis Brown, nous examinons la structure d'algèbre de Hopf des multizêtas motiviques cyclotomiques, qui sont des périodes motiviques du groupoïde fondamental de la droite projective moins 0, l'infini et les racines Nèmes de l'unité. Par application d'un morphisme période surjectif (conjecturé isomorphisme), nous pouvons déduire des résultats (identités, familles génératrices, etc.) sur les multizêtas cyclotomiques (complexes). La coaction de cette algèbre de Hopf (formule combinatoire explicite) est duale à l'action d'un dénommé groupe de Galois motivique sur ces périodes motiviques. Ces recherches sont ainsi motivées par l'espoir d'une théorie de Galois pour les périodes, étendant la théorie de Galois usuelle pour les nombres algébriques. (i) Nous présentons de nouvelles relations entre les sommes d'Euler (N=2) motiviques et deux nouvelles bases (conjecturées identiques) pour les multizêtas motiviques (N=1): Hoffman star (sous une conjecture analytique) et une seconde via les sommes d'Euler motiviques. (ii) Nous appliquons des idées de descentes galoisiennes à l'étude de ces périodes, en regardant notamment comment les multizêtas motiviques relatifs aux racines N' èmes de l'unité se plongent dans ceux associés aux racines Nèmes, lorsque N' divise N. Après avoir fourni des critères généraux, nous nous tournons vers les cas N égal à 2,3,4,6, 8, pour lesquels le groupoïde fondamental motivique engendre la catégorie des motifs de Tate mixtes sur l'anneau des entiers du Nème corps cyclotomique ramifié en N (non ramifié pour 6). Pour ces valeurs, nous explicitons les descentes galoisiennes, et étendons les résultats de Pierre Delign

Périodes du groupe fondamental motivique de la droite projective moins zero, l’infini et les racines n-èmes de l’unité

En s'inspirant du point de vue adopté par Francis Brown, nous examinons la structure d'algèbre de Hopf des multizêtas motiviques cyclotomiques, qui sont des périodes motiviques du groupoïde fondamental de la droite projective moins 0, l'infini et les racines Nèmes de l'unité. Par application d'un morphisme période surjectif (conjecturé isomorphisme), nous pouvons déduire des résultats (identités, familles génératrices, etc.) sur les multizêtas cyclotomiques (complexes). La coaction de cette algèbre de Hopf (formule combinatoire explicite) est duale à l'action d'un dénommé groupe de Galois motivique sur ces périodes motiviques. Ces recherches sont ainsi motivées par l'espoir d'une théorie de Galois pour les périodes, étendant la théorie de Galois usuelle pour les nombres algébriques. (i) Nous présentons de nouvelles relations entre les sommes d'Euler (N=2) motiviques et deux nouvelles bases (conjecturées identiques) pour les multizêtas motiviques (N=1): Hoffman star (sous une conjecture analytique) et une seconde via les sommes d'Euler motiviques. (ii) Nous appliquons des idées de descentes galoisiennes à l'étude de ces périodes, en regardant notamment comment les multizêtas motiviques relatifs aux racines N' èmes de l'unité se plongent dans ceux associés aux racines Nèmes, lorsque N' divise N. Après avoir fourni des critères généraux, nous nous tournons vers les cas N égal à 2,3,4,6, 8, pour lesquels le groupoïde fondamental motivique engendre la catégorie des motifs de Tate mixtes sur l'anneau des entiers du Nème corps cyclotomique ramifié en N (non ramifié pour 6). Pour ces valeurs, nous explicitons les descentes galoisiennes, et étendons les résultats de Pierre DeligneFollowing F. Brown's point of view, we look at the Hopf algebra structure of motivic cyclotomic multiple zeta values, which are motivic periods of the fundamental groupoid of the projective line minus 0, infinity and N roots of unity. By application of a surjective period map (conjectured isomorphism), we deduce results (generating families, identities, etc.) on cyclotomic multiple zeta values, which are complex numbers. The coaction of this Hopf algebra (explicit combinatorial formula) is the dual of the action of a so-called motivic Galois group on these specific motivic periods. This entire study was motivated by the hope of a Galois theory for periods, which should extend the usual one for algebraic numbers.(i)In the first part, we focus on the case of motivic multiple zeta values (N = 1) and Euler sums (N = 2). In particular, we present new bases for motivic multiple zeta values: one via motivic Euler sums, and another (depending on an analytic conjecture) which is known as the Hoffman star basis; under a general motivic identity that we conjecture, these bases are identical.\u2028(ii)In the second part, we apply some Galois descents ideas to the study of these periods, and examine how multiple zeta values relative to N' roots of unity are embedded into those relative to N roots, when N' divide N. After giving some general criteria for any N, we focus on the cases N=2,3,4, 6, 8, for which the motivic fundamental group generates the category of mixed Tate motives on the ring of integer of the N cyclotomic field ramified in N (unramified if N=6). For those N, we are able to construct Galois descents explicitly, and extend P. Deligne's results

Learning Fair Policies in Decentralized Cooperative Multi-Agent Reinforcement Learning

We consider the problem of learning fair policies in (deep) cooperative multi-agent reinforcement learning (MARL). We formalize it in a principled way as the problem of optimizing a welfare function that explicitly encodes two important aspects of fairness: efficiency and equity. As a solution method, we propose a novel neural network architecture, which is composed of two sub-networks specifically designed for taking into account the two aspects of fairness. In experiments, we demonstrate the importance of the two sub-networks for fair optimization. Our overall approach is general as it can accommodate any (sub)differentiable welfare function. Therefore, it is compatible with various notions of fairness that have been proposed in the literature (e.g., lexicographic maximin, generalized Gini social welfare function, proportional fairness). Our solution method is generic and can be implemented in various MARL settings: centralized training and decentralized execution, or fully decentralized. Finally, we experimentally validate our approach in various domains and show that it can perform much better than previous methods.Comment: International Conference on Machine Learnin