Fuzzy-genetic hybrid models for large-horizon deterministic planning

Entity: Universitat Rovira i Virgili (URV)

Confidenciality: No

Education area(s): Enginyeria de la Seguretat Informàtica i Intel·ligència Artificial

APS: No

Title in different languages: Fuzzy-genetic hybrid models for large-horizon deterministic planning

Abstract: This thesis addresses deterministic planning problems with long horizons, motivated by the life simulation game Princess Maker 2. The formulation involves an agent with dozens of attributes, several dozen actions, and thousands of steps, leading to combinatorial explosion. Classical approaches such as automatic planning and reinforcement learning fail to scale. We propose a fuzzy-genetic hybrid method: fuzzy logic encodes domain knowledge as rules over latent parameters (“inclinations”), while genetic algorithms optimize them. Implemented in C++ with fuzzylite and pagmo, the solver successfully produces valid action sequences, demonstrating tractability where classical methods are impractical.

Subject: Lògica difusa

Academic year: 2024-2025

Language: en

Work's public defense date: 2025-09-15

Subject areas: Computer engineering

Student: Safronov, Mark

Department: Enginyeria Informàtica i Matemàtiques

Creation date in repository: 2026-03-13

TFM credits: 9

Keywords: automatic planning, fuzzy logic, evolutionary computations

Title in original language: Fuzzy-genetic hybrid models for large-horizon deterministic planning

Access Rights: info:eu-repo/semantics/openAccess

Project director: Duch Gavaldà, Jordi