Enhancing Non-Player Characters(NPC) Behaviourin Video Games Using Reinforcement Learning
Journal Title: International Journal of Innovations in Science and Technology - Year 2025, Vol 7, Issue 2
Abstract
NPCs enrich the immersive experience of a video game, and traditionally exist along purely rule-or script-based paradigms, denying adaptability or intelligent decision-making very often. The research integrates RL into the NPC behaviourto allow for the more realistic, dynamic interactions and responsive behaviourthat today's gaming environments require. We will review state-of-the-art RL algorithms and validate improvements implemented in our own RL model within a sandbox game environment into NPC decision-making and player engagement. According to our results, RL makes NPCs adaptive, tactically deep, and realistic while the classical ones fail. The study provides rigorous methodology and analysis to demonstrate the feasibility and advantages of using RL for the design of a new generation of games.
Authors and Affiliations
Mirza Shahveer Ayoub, Rabia Tehseen, Uzma Omer, Maham Mehr Awan, Rubab Javaid
Mininet-IDS: A Step Towards Reproducible Research for Machine Learning Based Intrusion Detection Systems
Software-Defined Networking (SDN) has revolutionized network management by enabling more flexible, programmable, and controlled networks. However, the SDN controller can be a target for attacks that could bring down th...
An IoT Distributive SM Controller for Mitigation of Circulating Currents Among Sources in a Standalone DC Microgrid
Sources of similar or different power ratings are connected in parallel within the DC microgrid. During operation, these sources generate circulating currents along with their normal currents, which disrup...
Development of a Machine Learning-Based Predictive System For Classifying Psoriasis
Psoriasis is a chronic autoimmune skin condition characterized by inflamed, flaky patches that affect both physical consolation and passionate well-being. Opportune and exact determination is basic for viable treatment;...
Explicit State Model Checking Effects on Learning-Based Testing
Exploring the impact of integrating an explicit state model checker into the learningbased testing (LBT) framework presents an intriguing challenge. Traditionally, LBT has leveraged symbolic model checkers such as NuSMV...
Heart Sense: A novel IoT integrated Deep Learning Based ECG Image Analysis forEnhanced Heart Disease Prediction
The IoT based advancements in the healthcare networks leveraging the unmatched capabilities of the Internet of Things for various fatal disease prediction and remote health monitoring that proved to be very beneficial...