GAIG Game AI Research Group @ QMUL



The Game AI Group at Queen Mary University of London will be presenting 12 papers, 1 demo and 1 tutorial at the IEEE Conference on Games 2020. Details on where each can be found will be updated in this post once available, and you may find full details on the conference website as well.


AI for Playing Games

Christopher Bamford and Simon Lucas Neural Game Engine: Accurate learning of generalizable forward models from pixels

Ivan Bravi and Simon Lucas Rinascimento: using event-value functions for playing Splendor

Raluca D. Gaina, Chiara F. Sironi, Mark H. M. Winands, Diego Perez Liebana and Simon Lucas Self-Adaptive Rolling Horizon Evolutionary Algorithms for General Video Game Playing

Diego Perez Liebana, Muhammad Sajid Alam and Raluca D. Gaina Rolling Horizon NEAT for General Video Game Playing

Martin Balla, Simon Lucas and Diego Perez Liebana Evaluating Generalization in General Video Game Playing

Alvaro Ovalle and Simon Lucas Bootstrapped model learning and error correction for planning with uncertainty in model-based RL

Alexander Dockhorn and Simon Lucas Local Forward Model Learning for GVGAI Games

Simon Lucas Demo Paper: Cross Platform Games in Kotlin

Education and Games

Jack Ratcliffe and Laurissa Tokarchuk Evidence for embodied cognition in immersive virtual environments using a second language learning environment

Game Design

Daniel Hernandez, Charles Takashi Toyin Gbadamosi, James Goodman and James Alfred Walker Metagame Autobalancing for Competitive Multiplayer Games

Rokas Volkovas, Michael Fairbank, John Woodward and Simon Lucas Practical Game Design Tool: State Explorer

PCG and AI for Game Design

Michael Cook Procedural Generation and Information Games

Michael Cook Software Engineering For Automated Game Design


Michael Cook Getting Started in Automated Game Design

Aug 25th: 14:00-14:30 BST Joint Q&A live session for the tutorial