An Unified Intelligence-Communication Model for Multi-Agent System
  Part-I: Overview
  Motivated by Shannon's model and recent rehabilitation of self-supervised
artificial intelligence having a "World Model", this paper propose an unified
intelligence-communication (UIC) model for describing a single agent and any
multi-agent system.
  Firstly, the environment is modelled as the generic communication channel
between agents. Secondly, the UIC model adopts a learning-agent model for
unifying several well-adopted agent architecture, e.g. rule-based agent model
in complex adaptive systems, layered model for describing human-level
intelligence, world-model based agent model. The model may also provide an
unified approach to investigate a multi-agent system (MAS) having multiple
action-perception modalities, e.g. explicitly information transfer and implicit
information transfer.
  This treatise would be divided into three parts, and this first part provides
an overview of the UIC model without introducing cumbersome mathematical
analysis and optimizations. In the second part of this treatise, case studies
with quantitative analysis driven by the UIC model would be provided,
exemplifying the adoption of the UIC model in multi-agent system. Specifically,
two representative cases would be studied, namely the analysis of a natural
multi-agent system, as well as the co-design of communication, perception and
action in an artificial multi-agent system. In the third part of this treatise,
the paper provides further insights and future research directions motivated by
the UIC model, such as unification of single intelligence and collective
intelligence, a possible explanation of intelligence emergence and a dual model
for agent-environment intelligence hypothesis.
  Notes: This paper is a Previewed Version, the extended full-version would be
released after being accepted.
