In my game theory course, we are working through many ways of ascertaining the optimal decision-making given the constraints of game rules on the decision-making context. We are learning the many different types of games and how the games are played. We are engaging sequential and synchronous games. We are looking at various conditional contexts. We are drawing game trees. We are engaging normal and strategic table structures. We are using various algebraic equations to figure out expected utilities of certain players within payoff matrices.
These endeavors are all very fun and precisely rigorous. I have to make sure that when I solve an equation (yes, back to 7th grade), I have to make sure not to introduce error. I have to ensure that I’m carrying numbers correctly. Revisiting algebra is almost like re-learning a foreign language with which one has a history—there is that degree of symbolism and abstraction. That comfort level with symbols and abtractions makes for an easier transfer of concepts.
Using reverse induction methods of analysis, I have to make sure that I can mix the reality of a story problem with the mathematically-expressed logic of the decision-making and to make sure that they align. Here, we use story to rationalize the likely decision-making to eradicate unlikely threats.
These models have their limits. They focus on very thin-sliced aspects of decision-making without considering other known information about human-decision-making and the particular (often-evolving) context, but that’s how it should be…because models are parsimonious. And no one apparently only applies one model in decision-making. Most apply multiple models to understand a phenomena. There are clearly limits of what a method can reveal about a context. Factors are always missing, and the actual defined relationships are limited.
I have always found decision-making to be an intriguing aspect of human cognition. There’s a lot of writing in the literature that shows how crisis situations may change human perception and decision-making. Decision-support systems in information and communication technologies (ICT) have to consider so many aspects of human thinking in their design—in order to be useful.
Decision supports are a few steps ahead of decision-making. This latter approach has to anticipate understandings, mental models, decision-making junctures, and user needs…and it has to offer accurate interventions that do not cause negative learning or poor decision-making. When I signed on to the course, I had not really thought through some of the interconnections between game theory and decision-support-systems, which I’ve observed from a distance for years. It’s helpful to see some of the overlaps.