AI4G-7-Planning.pdf

Lecture Notes on Artificial Intelligence for Games Summer Semester 2024 Deterministic Planning Script © 2020 Matthias Schubert Deterministic Problems in Games very few deterministic games are interesting solving subtasks for AI Engines: –...

Lecture Notes on Artificial Intelligence for Games Summer Semester 2024 Deterministic Planning Script © 2020 Matthias Schubert Deterministic Problems in Games very few deterministic games are interesting solving subtasks for AI Engines: – find exits of a building – route to a target approximate and heuristic solutions for non-deterministic problems often rely on making the problem deterministic and then solve the deterministic solution example: assume that the opponent uses the identical policy as the player in Go or chess. Artificial Intelligence for Games 2 Deterministic Sequential Planning assume : static and fully-observable environments set of states S = {s1,..,sn} Set of actions A(s) for each state sÎS reward function R: R(s) (if negative = cost function) transition function T: S´A => S: t(s,a) = s’ goal: maximize cumulated rewards (minimize cumulated cost) cumulated reward/cost of the episode: ∑$!"# 𝛾 ! 𝑟! with 0 < 𝛾 ≤ 1 (𝛾=1: all rewards count the same, 𝛾