Quantum Entanglement-Based Information Encoding and Multi-Agent Collaborative Decision-Making

Abstract

This paper explores the application of quantum entanglement for information encoding and multi-agent collaborative decision-making. We propose a novel framework where multiple agents leverage entangled quantum processors to share information instantaneously, overcoming the limitations of classical communication channels in terms of bandwidth and latency. The core concept involves each agent utilizing its quantum processor to process information derived from the entangled state, combined with local information, to make decisions. These decisions are then used to update the entangled state, facilitating a dynamic and adaptive collaborative process. The theoretical analysis demonstrates that this approach can achieve decision-making capabilities surpassing those attainable through conventional communication methods, offering enhanced system adaptability and robustness. Specifically, we introduce the following key equations to represent the core mechanisms: Let $I_i(t)$ be the local information held by agent $i$ at time $t$. Let $E_i(t)$ be the entangled state shared by agent $i$ at time $t$. The decision function for agent $i$ at time $t$ is defined as: $D_i(t) = f(I_i(t), E_i(t))$ where $f$ is a decision function. The update rule for the entangled state $E_i(t)$ based on the decision $D_i(t)$ and local information $I_i(t)$ is given by: $E_i(t+1) = g(E_i(t), D_i(t), I_i(t))$ where $g$ is an update function. The overall system objective can be represented as: $\max_{D_1(t), D_2(t), ..., D_K(t)} \sum_{i=1}^{K} \phi(D_i(t))$ where $\phi$ is an objective function. This research highlights the potential of quantum entanglement to revolutionize multi-agent systems, paving the way for fundamentally new collaborative strategies with superior performance. ---