Conference

DanZero: Mastering GuanDan Game with Reinforcement Learning

The use of artificial intelligence (AI) in card games has been a widely researched topic in the field of AI for an extended period. Recent advancements have led to AI programs exhibiting expert-level gameplay in complex card games such as Mahjong, …

Evolution of Walsh Transforms with genetic programming

The design of Boolean functions which exhibit high-quality cryptography properties is a crucial aspect when implementing secure stream ciphers. To this end, several methods have been proposed to search for secure Boolean functions, and, among those, …

Examining the Role of Incentives in Scholarly Publishing with Multi-Agent Reinforcement Learning

Scientific research plays a crucial role in advancing human civilization, thanks to the efforts of a multitude of individual actors. Their behavior is largely driven by individual incentives, both explicit and implicit. In this paper, we propose and …

Compressing and Comparing the Generative Spaces of Procedural Content Generators

The past decade has seen a rapid increase in the level of research interest in procedural content generation (PCG) for digital games, and there are now numerous research avenues focused on new approaches for driving and applying PCG systems. An area …

A generalizability measure for program synthesis with genetic programming

The generalizability of programs synthesized by genetic programming (GP) to unseen test cases is one of the main challenges of GP-based program synthesis. Recent work showed that increasing the amount of training data improves the generalizability of …

Model Learning with Personalized Interpretability Estimation (ML-PIE)

High-stakes applications require AI-generated models to be interpretable. Current algorithms for the synthesis of potentially interpretable models rely on objectives or regularization terms that represent interpretability only coarsely (e.g., model …

DAE-GP: denoising autoencoder LSTM networks as probabilistic models in estimation of distribution genetic programming

Estimation of distribution genetic programming (EDA-GP) algorithms are metaheuristics where sampling new solutions from a learned probabilistic model replaces the standard mutation and recombination operators of genetic programming (GP). This paper …

Synthesis through unification genetic programming

We present a new method, Synthesis through Unification Genetic Programming (STUN GP), which synthesizes provably correct programs using a Divide and Conquer approach. This method first splits the input space by undergoing a discovery phase that uses …

Communication in Decision Making: Competition favors Inequality

We consider a multi-agent system in which the individual goal is to collect resources, but where the amount of collected resources depends also on others decision. Agents can communicate and can take advantage of being communicated other agents' …

Evolution of Distributed Neural Controllers for Voxel-based Soft Robots

Voxel-based soft robots (VSRs) are aggregations of elastic, cubic blocks that have sparkled the interest of Robotics and Artificial Life researchers. VSRs can move by varying the volume of individual blocks, according to control signals dictated by a …