GAIG
Game AI Research Group @ QMUL
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Rolling Horizon Evolutionary Algorithms
Start year:
2016
Funded by:
EPSRC (IGGI CDT, partly-funded)
Members involved
Raluca Gaina
Simon Lucas
Diego Perez Liebana
Building general AI players based on Evolutionary Algorithms.
Core associated publications
Analysis of Vanilla Rolling Horizon Evolution Parameters in General Video Game Playing
Bandit-based random mutation hill-climbing
Population Seeding Techniques for Rolling Horizon Evolution in General Video Game Playing
Rolling Horizon Evolution Enhancements in General Video Game Playing
Introducing Real World Physics and Macro-Actions to General Video Game AI
VERTIGO: Visualisation of Rolling Horizon Evolutionary Algorithms in GVGAI
Tackling Sparse Rewards in Real-Time Games with Statistical Forward Planning Methods
Related publications
Efficient Evolutionary Methods for Game Agent Optimisation: Model-Based is Best
Project Thyia: A Forever Gameplayer
General Win Prediction from Agent Experience
Beyond Playing to Win: Diversifying Heuristics for GVGAI
GAIG Projects
GVGAI
IG-PCG
IG-SFP
IG-TAG
Java-Pommerman
RHEA
rhNEAT
TAG
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