UBCL: A Reinforcement Learning Framework for Controllable and Diverse Player Behaviors

arXiv:2512.10835 · cs.LG · Submitted 2025-12-11 · Read on arXiv

cs.LG

Submitted: 2025-12-11

Updated: 2026-09-10

Comments: Accepted version. Published in IEEE Transactions on Games

Journal ref: IEEE Transactions on Games, early access, 2026

DOI: 10.1109/TG.2026.3703355

License: http://arxiv.org/licenses/nonexclusive-distrib/1.0/

Terminology

• Reinforcement Learning — 19× in this paper · explained in 4 episodes
• Actor — 6× in this paper · explained in 3 episodes
• Reward Function — 5× in this paper · explained in 2 episodes
• AI Agents — 3× in this paper · explained in 2 episodes
• Deep Reinforcement Learning — 3× in this paper · explained in 2 episodes
• Fidelity — 3× in this paper · explained in 2 episodes
• IEEE Conference on Games — 3× in this paper
• Reward Shaping — 3× in this paper · explained in 2 episodes
• Transformer — 3× in this paper · explained in 2 episodes
• Accuracy — 2× in this paper · explained in 1 episode
• Alignment — 2× in this paper · explained in 1 episode
• Archetype — 2× in this paper · explained in 1 episode
• Proximal Policy Optimization — 2× in this paper
• Artificial Intelligence (AI) — 1× in this paper · explained in 2 episodes
• Benchmark — 1× in this paper · explained in 2 episodes
• Combinatorial Optimization — 1× in this paper · explained in 2 episodes
• Cooperation — 1× in this paper · explained in 2 episodes
• Diffusion Model — 1× in this paper · explained in 8 episodes
• Diffusion Models — 1× in this paper · explained in 6 episodes
• Meta-learning — 1× in this paper · explained in 2 episodes
• Personalization — 1× in this paper · explained in 2 episodes
• Principal Component Analysis — 1× in this paper
• Principal Component Analysis (PCA) — 1× in this paper · explained in 4 episodes
• Proximal Policy Optimization (PPO) — 1× in this paper · explained in 4 episodes
• Regularization — 1× in this paper · explained in 3 episodes
• Reinforcement Learning (RL) — 1× in this paper · explained in 25 episodes

Sources

• Dota 2 with Large Scale Deep Reinforcement Learning
• Adversarial Imitation Learning On Aggregated Data
• Unity: A General Platform for Intelligent Agents
• Proximal Policy Optimization Algorithms
• Towards Human-Like RL: Taming Non-Naturalistic Behavior in Deep RL via Adaptive Behavioral Costs in 3D Games
• Trust Region Policy Optimization
• Continuous control with deep reinforcement learning

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