Multiagent-Prediction-Reward is a research-oriented framework that integrates prediction models and reward distribution mechanisms for multi-agent reinforcement learning. It includes environment wrappers, neural modules for forecasting peer actions, and customizable reward routing logic that adapts to agent performance. The repository provides configuration files, example scripts, and evaluation dashboards to run experiments on cooperative tasks. Users can extend the code to test novel reward functions, integrate new environments, and benchmark against established multi-agent RL algorithms.

CulturePulse leverages multi-agent AI-created digital twins to predict consumer behavior across 93 psychological and cultural dimensions. This allows businesses to fine-tune their messaging to resonate deeply with specific audience segments. Features include A/B testing, audience insights, and resonance scoring, aiding marketers in crafting content that aligns with their audience’s values, beliefs, and behaviors. CulturePulse transforms raw data into actionable insights, ensuring your messaging connects effectively and drives persistent engagement.