Poster Session (in Gather)

How to enter in Gather

  1. Be sure that you use Google Chrome or Firefox
  2. Follow this link and enter the password provided by the organizers to enter the space.
  3. Enjoy!

What you find in Gather

In Gather you will enter in the main room, where you can chat and do some networking.

Main room

At the left you will find the student poster room and at the right the regular poster and late-breaking abstract room (see below). In these rooms each poster is placed in a coordinate represented by a letter (column) and a number (row). You will find the posters associated to each position at the end of this page.

In the student poster room you will also find there counters (in the top, right and left walls) with the text “Vote here”, where you can vote for the best student poster. Use the registration code that was sent to you to vote (you can only vote for one poster).

Counter to vote for the best student poster (there are three of them)

Regular and LBA poster positions

  • A1 – On Restricting Real-Valued Genotypes in Evolutionary Algorithms (Jørgen Nordmoen) – EvoApplications (EvoAPPS)
  • A2 – EDM-DRL: Toward Stable Reinforcement Learning through Ensembled Directed Mutation (Michael Prince (TBD with other poster)) – EvoApplications (EvoAPPS)
  • A3 – A Multi-Objective Evolutionary Algorithm Approach for Optimizing Part Quality Aware Assembly Job Shop Scheduling Problems (Michael Prince) – EvoApplications (EvoAPPS)
  • A4 – Real Time Optimisation of Traffic Signals to Prioritise Public Transport (Milan Wittpohl) – EvoApplications (EvoAPPS)
  • A5 – Optimising diversity in classifier ensembles of classification trees (Carina Ivascu) – EvoApplications (EvoAPPS)
  • B1 – Evolving Character-Level DenseNet Architectures using Genetic Programming (Trevor Londt) – EvoApplications (EvoAPPS)
  • B2 – On the Effects of Absumption for XCS with Continuous-Valued Inputs (Alexander R. M. Wagner) – EvoApplications (EvoAPPS)
  • B3 – Automated, Explainable Rule Extraction from MAP-Elites archives (Neil Urquhart) – EvoApplications (EvoAPPS)
  • B4 – Estimation of Grain-level Residual Stresses in a Quenched Cylindrical Sample of Aluminium Alloy AA5083 using Genetic Programming (Laura Millán García) – EvoApplications (EvoAPPS)
  • B5 – EDA-Based Optimization of Blow-Off Valve Positions for Centrifugal Compressor Systems (Jacob Spindler) – EvoApplications (EvoAPPS)
  • C1 – Bayesian Networks for Mood Prediction Using Unobtrusive Ecological Momentary Assessments (Margarita Rebolledo) – EvoApplications (EvoAPPS)
  • C2 – Evolutionary Planning in Latent Space (Rasmus Berg Palm) – EvoApplications (EvoAPPS)
  • C3 – Event-driven multi-algorithm optimization: mixing Swarm and Evolutionary strategies (Juan J Merelo Guervos) – EvoApplications (EvoAPPS)
  • C4 – Utilizing the Untapped Potential of Indirect Encoding for Neural Networks with Meta Learning (Adam Katona) – EvoApplications (EvoAPPS)
  • C5 – EvoCraft: A New Challenge for Open-Endedness (Djordje Grbic) – EvoApplications (EvoAPPS)
  • D1 – “What is human?” A Turing Test for artistic creativity. (Antonio Daniele) – EvoMUSART
  • D2 – Exploring the Effect of Sampling Strategy on Movement Generation with Generative Neural Networks (Benedikte Wallace) – EvoMUSART
  • D3 – An Application for Evolutionary Music Composition using Autoencoders (Robert Neil McArthur) – EvoMUSART
  • D4 – Multi-objective workforce allocation in construction projects (Andrew Iskandar) – EvoApplications (EvoAPPS)
  • D5 – Continuous Ant-Based Neural Topology Search (AbdElRahman ElSaid) – EvoApplications (EvoAPPS)
  • E1 – A Multi-Objective Evolutionary Approach to Identify Relevant Audio Features for Music Segmentation (Igor Vatolkin) – EvoMUSART
  • E2 – Co-Create Drawing with One-Shot Generative Models (Sabine Wieluch) – EvoMUSART
  • E3 – Mixed-Initiative Level Design with RL Brush (Omar Delarosa) – EvoMUSART
  • E4 – Sensitivity to Partial Lamarckism in a Memetic Algorithm for Constrained Portfolio Optimization (Feijoo Colomine Duran) – Late-Breaking Abstracts (LBAs)
  • E5 – Modelling Asthma Patients’ Responsiveness to Treatment Using Feature Selection and Evolutionary Computation (Alberto Tonda) – EvoApplications (EvoAPPS)
  • F1 – Creating a Digital Mirror of Creative Practice (Colin Johnson) – EvoMUSART
  • F2 – From Music to Image – A Computational Creativity Approach (Luís Ricardo dos Santos Aleixo) – EvoMUSART
  • F3 – A Swarm Grammar-Based Approach to Virtual World Generation (Yasin Raies) – EvoMUSART
  • F4 – Short-term effects of weight initialization functions in Deep NeuroEvolution (Lucas Gabriel Coimbra Evangelista) – Late-Breaking Abstracts (LBAs)
  • F5 – Using a bio-inspired model to facilitate the ecosystem of data sharing in smart healthcare (Yao Yao) – Late-Breaking Abstracts (LBAs)
  • G1 – Mining Feature Relationships in Data (Andrew Lensen) – EuroGP
  • G2 – Incremental Evaluation in Genetic Programming (W B Langdon) – EuroGP
  • G3 – Progressive Insular Cooperative GP (Karina Brotto Rebuli) – EuroGP
  • G4 – Generating Music with Extreme Passages using GPT-2 (Berker Banar) – Late-Breaking Abstracts (LBAs)
  • G5 – Distributed species-based genetic algorithm for reinforcement learning problems (Anirudh Seth) – Late-Breaking Abstracts (LBAs)
  • H1 – On the Generalizability of Programs Synthesized by Grammar-Guided Genetic Programming (Dominik Sobania) – EuroGP
  • H2 – Probabilistic Grammatical Evolution (Jessica Mégane) – EuroGP
  • H3 – Evolving allocation rules for beam search heuristics in assembly line balancing (Marcus Ritt) – EuroGP
  • H4 – Getting a Head Start on Program Synthesis with Genetic Programming (Erik Hemberg) – EuroGP
  • H5 – Quantum fitness sharing in memetic algorithms for level design in Metroidvania games (Álvaro Gutiérrez Rodríguez) – Late-Breaking Abstracts (LBAs)

Student poster positions

  • A1 – Salp Swarm Optimization Search Based Feature Selection for Enhanced Phishing Websites Detection (Ruba Abu Khurma) – EvoApplications (EvoAPPS)
  • A2 – Improving Search Efficiency and Diversity of Solutions in Multiobjective Binary Optimization by Using Metaheuristics Plus Integer Linear Programming  (Miguel Ángel Domínguez Ríos) – EvoApplications (EvoAPPS)
  • A3 – A NEAT Visualisation of Neuroevolution Trajectories (Stefano Sarti) – EvoApplications (EvoAPPS)
  • A4 – Evolutionary Neural Architecture Search Supporting Approximate Multipliers (Michal Piňos) – EuroGP
  • B1 – Deep Optimisation: Multi-Scale Evolution by Inducing and Searching in Deep Representations (Jamie Caldwell) – EvoApplications (EvoAPPS)
  • B2 – Towards Explainable Exploratory Landscape Analysis: Extreme Feature Selection for Classifying BBOB Functions (Quentin Renau) – EvoApplications (EvoAPPS)
  • B3 – A multi-objective multi-type facility location problem for the delivery of personalised medicine (Andreea Avramescu) – EvoApplications (EvoAPPS)
  • B4 – Towards incorporating Human Knowledge in Fuzzy Pattern Tree Evolution (Aidan Murphy) – EuroGP
  • C1 – A Profile-Based ‘GrEvolutionary’ Hearthstone Agent (Antonio Mora García) – EvoApplications (EvoAPPS)
  • C2 – Improving Neuroevolution Using Island Extinction and Repopulation, An Experimental Study on the Effects of Weight Initialization and Weight Inheritance on Neuroevolution (Zimeng Lyu) – EvoApplications (EvoAPPS)
  • C3 – EA-based ASV Trajectory Planner for Pollution Detection in Lentic Waters (Gonzalo Carazo-Barbero) – EvoApplications (EvoAPPS)
  • C4 – Automatic design of deep neural networks applied to image segmentation problems (Ricardo Henrique Remes de Lima) – EuroGP
  • D1 – Identification of Pure Painting Pigment using Machine Learning Algorithms (Ailin Chen) – EvoMUSART
  • D2 – “A Good Algorithm Does Not Steal – It Imitates”: The Originality Report as a Means of Measuring When a Music Generation Algorithm Copies Too Much (Zongyu Yin) – EvoMUSART
  • D3 – Chord Embeddings: Analyzing What They Capture and Their Role for Next Chord Prediction and Artist Attribute Prediction (Allison Lahnala) – EvoMUSART
  • D4 – Hybridization of Racing Methods with Evolutionary Operators for Simulation Optimization of Traffic Lights Programs (Christian Cintrano) – EvoCOP
  • E1 – SyVMO: Synchronous Variable Markov Oracle for modeling and predicting multi-part musical structures (Nádia de Sousa Varela de Carvalho) – EvoMUSART
  • E2 – Interactive, Efficient and Creative Image Generation Using Compositional Pattern-Producing Networks (Erlend Gjesteland Ekern) – EvoMUSART
  • E3 – Decomposition-based Multi-objective Landscape Features and Automated Algorithm Selection (Cosson Raphaël) – EvoCOP
  • E4 – Stagnation Detection with Randomized Local Search (Amirhossein Rajabi) – EvoCOP