The Definition of AI in Terms of Multi Agent Systems
This work provides a theoretical reframing of AI for researchers in multi-agent systems, but it is incremental as it presents an old answer in a new form.
The paper tackles the problem of defining AI by proposing a definition in terms of multi-agent systems, aiming to help create programs that can model their environment, with the result that multi-agent models are more natural and easier to discover than single-agent ones.
The questions which we will consider here are "What is AI?" and "How can we make AI?". Here we will present the definition of AI in terms of multi-agent systems. This means that here you will not find a new answer to the question "What is AI?", but an old answer in a new form. This new form of the definition of AI is of interest for the theory of multi-agent systems because it gives us better understanding of this theory. More important is that this work will help us answer the second question. We want to make a program which is capable of constructing a model of its environment. Every multi-agent model is equivalent to a single-agent model but multi-agent models are more natural and accordingly more easily discoverable.