Artificial Intelligence and Robotics

Biography

Biography: Jose B. Cruz Jr

Abstract

We focus on the decision-making aspect of artifi cial intelligence in cyber-physical systems. According to NSF, cyberphysical
systems are engineered systems that are built from and depend upon, the seamless integration of computational
algorithms and physical components. Generally, there are multiple decision-making entities (multi-agents) in such systems.
We highlight the presence of multi-agents with diff erent objectives by defi ning these as complex cyber-physical systems
(CCPS). Multi-agents are implemented as intelligent computers. Th ere is relatively less attention on multiple decision-making
entities in the cyber-physical systems and in the artifi cial intelligence literatures. In this presentation we attempt to stimulate
the artifi cial intelligence community to broaden the scope of their research to include work on CCPS. Much of the underlying
basis of CCPS is nonzero-sum dynamic game theory. With very few exceptions, the theory involves simplifying assumptions
that result in problems that are mathematically tractable. In the fi rst part of the presentation, we provide an overview of these
results. In the second part of the presentation we explore trends on how some of the simplifi cations might be relaxed to increase
the scope of applications. One simplifying assumption is that the CCPS has a single mathematical model that is known to all
decision-making entities. In realistic applications, each decision-making entity constructs its own mathematical model, known
only to itself, of the same CCPS. Another simplifying assumption is that each decision-making entity knows the objective
function of each decision-making entity. We consider a parameterization concept to relax these assumptions. We illustrate
parameterization in an electric power network