DiGRA/FDG '16 - Abstract Proceedings of the First International Joint Conference of DiGRA and FDG
Dundee, Scotland: Digital Games Research Association and Society for the Advancement of the Science of Digital Games, August, 2016
Number: 2
Volume: 13
ISBN / ISNN: ISSN 2342-9666
In this work we discuss a stochastic extension to the (discrete) Belief-Driven Pathfinding (BDP) approach for finding personalized paths based on the beliefs of a character about the current state of the map. Our stochastic BDP upgrades previous work to the more realistic setting of using probabilities for the beliefs and takes advantage of approximate Monte Carlo Tree Search approaches.