On merging and dividing of Barabási-Albert-graphs. - Pascal Held; Alexander Dockhorn; Rudolf Kruse (EALS, 2014)

Generating Events for Dynamic Social Network Simulations. - Pascal Held; Alexander Dockhorn; Rudolf Kruse (IPMU (2), 2014)

Clustering Social Networks Using Competing Ant Hives. - Pascal Held; Alexander Dockhorn; Benjamin Krause; Rudolf Kruse (ENIC, 2015)

An Alternating Optimization Approach Based on Hierarchical Adaptations of DBSCAN. - Alexander Dockhorn; Christian Braune; Rudolf Kruse (SSCI, 2015)

On Merging and Dividing Social Graphs. - Pascal Held; Alexander Dockhorn; Rudolf Kruse (J. Artif. Intell. Soft Comput. Res., 2015)

Variable density based clustering. - Alexander Dockhorn; Christian Braune; Rudolf Kruse (SSCI, 2016)

Combining cooperative and adversarial coevolution in the context of pac-man. - Alexander Dockhorn; Rudolf Kruse (CIG, 2017)

A decision heuristic for Monte Carlo tree search doppelkopf agents. - Alexander Dockhorn; Christoph Doell; Matthias Hewelt; Rudolf Kruse (SSCI, 2017)

Using a multiobjective genetic algorithm for curve approximation. - Tim Sabsch; Christian Braune; Alexander Dockhorn; Rudolf Kruse (SSCI, 2017)

Forward Model Approximation for General Video Game Learning. - Alexander Dockhorn; Daan Apeldoorn (CIG, 2018)

Predicting Opponent Moves for Improving Hearthstone AI. - Alexander Dockhorn; Max Frick; Ünal Akkaya; Rudolf Kruse (IPMU (2), 2018)

Model Decomposition for Forward Model Approximation. - Alexander Dockhorn; Tim Tippelt; Rudolf Kruse (SSCI, 2018)

Learning Local Forward Models on Unforgiving Games. - Alexander Dockhorn; Simon M. Lucas; Vanessa Volz; Ivan Bravi; Raluca D. Gaina; Diego Perez Liebana (CoG, 2019)

A Local Approach to Forward Model Learning: Results on the Game of Life Game. - Simon M. Lucas; Alexander Dockhorn; Vanessa Volz; Chris Bamford 001; Raluca D. Gaina; Ivan Bravi; Diego Pérez-Liébana; Sanaz Mostaghim; Rudolf Kruse (CoG, 2019)

Fuzzy Multiset Clustering for Metagame Analysis. - Alexander Dockhorn; Tony Schwensfeier; Rudolf Kruse (EUSFLAT Conf., 2019)

Introducing the Hearthstone-AI Competition. - Alexander Dockhorn; Sanaz Mostaghim (CoRR, 2019)

STRATEGA: A General Strategy Games Framework. - Alexander Dockhorn; Jorge Hurtado Grueso; Dominik Jeurissen; Diego Perez Liebana (AIIDE Workshops, 2020)

TAG: A Tabletop Games Framework. - Raluca D. Gaina; Martin Balla; Alexander Dockhorn; Raúl Montoliu; Diego Perez Liebana (AIIDE Workshops, 2020)

Local Forward Model Learning for GVGAI Games. - Alexander Dockhorn; Simon M. Lucas (CoG, 2020)

Forward Model Learning for Motion Control Tasks. - Alexander Dockhorn; Rudolf Kruse (IEEE Conf. on Intelligent Systems, 2020)

The Design Of "Stratega": A General Strategy Games Framework. - Diego Perez Liebana; Alexander Dockhorn; Jorge Hurtado Grueso; Dominik Jeurissen (CoRR, 2020)

Design and Implementation of TAG: A Tabletop Games Framework. - Raluca D. Gaina; Martin Balla; Alexander Dockhorn; Raúl Montoliu; Diego Perez Liebana (CoRR, 2020)

Predicting Cards Using a Fuzzy Multiset Clustering of Decks. - Alexander Dockhorn; Rudolf Kruse (Int. J. Comput. Intell. Syst., 2020)

Prediction-based search for autonomous game-playing - Alexander Dockhorn (2020)

Vorhersagebasierte Suche für autonomes Spielen. - Alexander Dockhorn (Ausgezeichnete Informatikdissertationen, 2020)

Portfolio Search and Optimization for General Strategy Game-Playing. - Alexander Dockhorn; Jorge Hurtado Grueso; Dominik Jeurissen; Linjie Xu; Diego Perez Liebana (CEC, 2021)

Game State and Action Abstracting Monte Carlo Tree Search for General Strategy Game-Playing. - Alexander Dockhorn; Jorge Hurtado Grueso; Dominik Jeurissen; Linjie Xu; Diego Perez Liebana (CoG, 2021)

Multi-Objective Optimization and Decision-Making in Context Steering. - Alexander Dockhorn; Sanaz Mostaghim; Martin Kirst; Martin Zettwitz (CoG, 2021)

Generating Diverse and Competitive Play-Styles for Strategy Games. - Diego Pérez-Liébana; Cristina Guerrero-Romero; Alexander Dockhorn; Linjie Xu; Jorge Hurtado Grueso; Dominik Jeurissen (CoG, 2021)

Modellheuristiken für effizientes forward model learning. - Alexander Dockhorn; Rudolf Kruse (Autom., 2021)

Generating Diverse and Competitive Play-Styles for Strategy Games. - Diego Pérez-Liébana; Cristina Guerrero-Romero; Alexander Dockhorn; Dominik Jeurissen; Linjie Xu (CoRR, 2021)

Exception-Tolerant Hierarchical Knowledge Bases for Forward Model Learning. - Daan Apeldoorn; Alexander Dockhorn (IEEE Trans. Games, 2021)

Association Rule Mining for Unknown Video Games. - Alexander Dockhorn; Chris Saxton; Rudolf Kruse (Fuzzy Approaches for Soft Computing and Approximate Reasoning, 2021)

Balancing Exploration and Exploitation in Forward Model Learning. - Alexander Dockhorn; Rudolf Kruse (Advances in Intelligent Systems Research and Innovation, 2022)

Generalizations of Steering - A Modular Design. - Lars Wagner; Christopher Olson; Alexander Dockhorn (CoG, 2022)

Elastic Monte Carlo Tree Search with State Abstraction for Strategy Game Playing. - Linjie Xu; Jorge Hurtado Grueso; Dominic Jeurissen; Diego Perez Liebana; Alexander Dockhorn (CoG, 2022)

Choosing Representation, Mutation, and Crossover in Genetic Algorithms. - Alexander Dockhorn; Simon Lucas 001 (IEEE Comput. Intell. Mag., 2022)

AutoRL Hyperparameter Landscapes. - Aditya Mohan; Carolin Benjamins; Konrad Wienecke; Alexander Dockhorn; Marius Lindauer (AutoML, 2023)

Genetic Assessment Agent for High-School Student and Machine Co-Learning Model Construction on Computational Intelligence Experience. - Chang-Shing Lee; Mei-Hui Wang; Chih-Yu Chen; Fu-Jie Yang; Alexander Dockhorn (CEC, 2023)

Evolutionary Optimization of Baba Is You Agents. - Christopher Olson; Lars Wagner; Alexander Dockhorn (CEC, 2023)

Evolutionary Algorithm for Parameter Optimization of Context-Steering Agents. - Alexander Dockhorn; Martin Kirst; Sanaz Mostaghim; Martin Wieczorek; Heiner Zille (IEEE Trans. Games, 2023)

AI-Explained (Part I) [Guest Editorial]. - Pau-Choo Chung; Alexander Dockhorn; Jen-Wei Huang (IEEE Comput. Intell. Mag., 2023)

Elastic Monte Carlo Tree Search. - Linjie Xu; Alexander Dockhorn; Diego Perez Liebana (IEEE Trans. Games, 2023)

Personalized Dynamic Difficulty Adjustment Imitation Learning Meets Reinforcement Learning. - Ronja Fuchs; Robin Gieseke; Alexander Dockhorn (CoG, 2024)

Online Optimization of Curriculum Learning Schedules using Evolutionary Optimization. - Mohit Jiwatode; Leon Schlecht; Alexander Dockhorn (CoG, 2024)

Match Point AI: A Novel AI Framework for Evaluating Data-Driven Tennis Strategies. - Carlo Nübel; Alexander Dockhorn; Sanaz Mostaghim (CoG, 2024)

Markov Senior - Learning Markov Junior Grammars to Generate User-specified Content. - Mehmet Kayra Oguz; Alexander Dockhorn (CoG, 2024)

Strategy Game-Playing with Size-Constrained State Abstraction. - Linjie Xu; Diego Perez Liebana; Alexander Dockhorn (CoG, 2024)

Higher Replay Ratio Empowers Sample-Efficient Multi-Agent Reinforcement Learning. - Linjie Xu; Zichuan Liu; Alexander Dockhorn; Diego Perez Liebana; Jinyu Wang; Lei Song 001; Jiang Bian 002 (CoG, 2024)

AbstractSwarm Multi-Agent Logistics Competition: Multi-Agent Collaboration for Improving A Priori Unknown Logistics Scenarios. - Daan Apeldoorn; Alexander Dockhorn; Torsten Panholzer (GECCO Companion, 2024)

From Code to Play: Benchmarking Program Search for Games Using Large Language Models. - Manuel Eberhardinger; James Goodman 004; Alexander Dockhorn; Diego Perez Liebana; Raluca D. Gaina; Duygu Çakmak; Setareh Maghsudi; Simon M. Lucas (CoRR, 2024)

Guest Editorial: AI-eXplained (Part II) [Guest Editorial]. - Pau-Choo Chung; Alexander Dockhorn; Jen-Wei Huang (IEEE Comput. Intell. Mag., 2024)

A Survey of Non-Learning-Based Abstractions for Sequential Decision-Making. - Robin Schmöcker; Alexander Dockhorn (IEEE Access, 2025)

AI-based character generation for disease stories: a case study using epidemiological data to highlight preventable risk factors. - Sarah Mittenentzwei; Laura A. Garrison; Beatrice Budich; Kai Lawonn; Alexander Dockhorn; Bernhard Preim; Monique Meuschke (i-com, 2025)

Time-critical and confidence-based abstraction dropping methods. - Robin Schmöcker; Lennart Kampmann; Alexander Dockhorn (CoRR, 2025)

Explaining Neural Style Transfer [AI-eXplained]. - Chun-Hao Yang; Yi-Sheng Liao; Chun-Rong Huang; Alexander Dockhorn (IEEE Comput. Intell. Mag., 2025)