Analyzing impact of US natural resource depletion through simulation
As an analyst, the most important question that we are facing in life today is something that all of our businesses and economies are interdependent upon. Natural resources. Oil. Gas. Energy. When will it run out? And what will happen to each of us when it does?
Step into a day as a military strategic analyst. Let me brief you on some information about what we’re doing about the what-if scenarios. Sentient World Simulation is a project involving the use of Purdue University’s extremely powerful real world simulator by the US Joint Forces Command in predicting and evaluating future events.
The system itself is called SEAS (Synthetic Environment for Analysis and Simulations). There are proposals to incorporate the world’s largest US computer research infrastructure using advanced computational tera-grid systems soon. For some added value, you should take a look at the research papers that have been generated in this line of study at SEAS.
So before doing a micro simulation of a scenario and the what-ifs using game theory…let’s talk about game theory and what it is. Game theory is the study of rational behavior among interdependent agents. We take these “agents” who represent people, companies, or countries and basically study how they interrelate and try to see what they tend to do in certain situations. Let’s reuse the term “agents” as it is game-theory speak.
Ok. When we’re talking about agents, several behaviors have been found to persist. Reward and motivation. A tenet in game theory is that if competition between agents is unfettered, no agent will get more than its added value in a game. And thus, added value itself will allow us to characterize the balance of power in the game. In other words, this characterization will lead us to an understanding of how a quantifiable pie is created and how it will be divided up.
Now that you have an idea of the pie analogy in game theory. Let’s set some more rules for the “game”. Agents in the game have a common interest in making the overall pie as large as possible. However, they have a competitive interest in maximizing their own share of the pie. The agent’s rational decisions will take into account the anticipation of their rival’s responses in the game. And since responses may be imperfect in that; like a chess game, the agents here will not always make the best moves. What I mean is that there is a measure of uncertainty within the game. And that it is a rule too.
In some follow-up posts, I will discuss some classic examples of Nash Equlibrium and what it dictates within some “games”/simulations. One of them is a classic prisoner’s dilemma in which two potential criminals are captured and one is being pushed to confess. Another is a large company against a small company in terms of whether which one should make the first move (eg, choose to be white or black in a chess game). And then we will get back into the analysis of the game involving agents who are dependent on natural resources.