Rinascimento: Playing Splendor-Like Games With Event-Value Functions

Author:

Bravi Ivan1ORCID,Lucas Simon1ORCID

Affiliation:

1. Department of Electrical Engineering and Computer Engineering, Queen Mary University of London, London, U.K.

Funder

Engineering and Physical Sciences Research Council Centre for Doctoral Training in Intelligent Games and Game Intelligence

IT Services Research group, Queen Mary University of London

Publisher

Institute of Electrical and Electronics Engineers (IEEE)

Subject

Electrical and Electronic Engineering,Artificial Intelligence,Control and Systems Engineering,Software

Reference26 articles.

1. Learning to utilize shaping rewards: A new approach of reward shaping;hu;Proc Int Conf Neural Inf Process,2020

2. Policy invariance under reward transformations: Theory and application to reward shaping;ng;Proc Int Conf Mach Learn,0

3. Knowledge-based fast evolutionary MCTS for general video game playing

4. Automated Playtesting With Procedural Personas Through MCTS With Evolved Heuristics

5. Learning Montezuma’s Revenge from a single demonstration;salimans,2018

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