Improving decision making skills through game theory analysis and technical sports

game theory

Integrating technical sports and in-depth analysis of game theory in the school’s curriculum is imperative given the fast pace of technical evolution in the world and the continuously increasing complexity of society.

We are all biologically determined to have specific characteristics and a potential to work and be competent in a number of fields. There are specific skills that are required to work in different fields (scientific or not): fast and accurate decision making given various situations, verbal skills, quantitative analysis and the ability to do mental computations, accurate proprioception and perception of external states which result in motor actions, to name only a few.

Our world will become exponentially more technologically complex as time passes. Jobs that today are needed and successful will not necessarily be in demand by the market in 20-30 years from now. In order to allow our society to have an adaptable work-force it will be very important to have individuals capable of both making high-value decisions and at least understanding technology, if not preferably creating it.

I see game theory lessons in school as adding significant value in making next generations capable of making better decisions, and technical sports as a way of attracting and selecting individuals in STEM.

Technical sports are practical activities which focus on improving abilities such as manuality, eye-hand coordination in executing high-precision operations required for building prototypes and controlling RC or autonomous systems. Encouraging sports activities is a
must for any country which shows even the slightest interest in actually guiding the youth in their career development.

An efficient way of recruiting high-potential young individuals which would later become scientists or technologists is through technical-applicative sports.

If a nation shows even a modest interest in guiding the youth for the purpose of choosing a career, options must be presented at an early stage: it is not something new that the most successful scientists and technologists are actually the ones having the talent to work in the

In Europe and the United States technical sports are not included in the common curriculum of schools. In the past in Eastern Europe they were the base for recruiting and training our specialists. As a side note such occupations were encouraged even before the communist regime, in Romania for example the Monarchy was funding clubs which were pursuing such sports (King Michael I of Romania was trained in his youth in such groups).

It was young people going through these groups to later become engineers and specialists capable of creating the best air superiority fighter plane in the world: the one which Romania used in WW2 against both the Russian aggressors and the fascist regimes.

Prototyping skills (including technological know-how), distributed attention and design abilities are needed in order to pursue technical-applicative sports. The Chinese government understood this and as such there are various competitions, clubs and other activities associated with such sports. Also technical know-how is gained in many schools through the educational system: for economists it looks like our work-force training is focused too much on theoretical knowledge (mostly memorizing facts) and practical skills are mostly omitted.

In any society there must be an equilibrium between occupational fields, and in a highly technological civilization STEM specialists are in high demand: it is natural for us to put effort into recruiting and preparing them to enter the work-force, given the benefits that
the society gains from their activities.

The other aspect that educational systems neglect is the coordinated use of simulators and games for improving the decision making skills of individuals. Combining game theory (a modern and productive field of research in economics) with digital technologies will allow us to also evaluate high value individuals, and further guide them in their careers.

Not all games are actually useful in this process. I believe that the vast majority of the developed games are not useful at all: low levels of attention required, very low complexity levels and repetitive activities are not what we want to see in education.

The games that I think that would be of high educational value are perfect information games such as Go and chess, real time strategy games (with complex game state spaces), and not-common games that require pattern recognition (preferably abstract).

Games such as chess require players to foresee future game states with large horizons (from 7-8 moves in advance for competent amateurs to 15 and above for the great players such as grandmasters).

Being a game of perfect information (all players having all the available information relevant for the play) the essence of the game is that of relatively quickly identifying the near-optimal actions required to advance to high value states from which a player is likely to win the game if it acts optimally.

Real strategy games (RTSs), some played on the esports arena, such as StarCraft, are much more complex games of imperfect information which beyond exact probabilistic strategic thinking require knowledge of tactics and abilities of identifying the best micro-actions (short command sequences) at any given moment from the available set of actions.

Competent RTS play requires quickly evaluating the economic evolution while using resource management skills, understanding of precise (at the level of fractions of the map length-scale in some cases) scouting of adversary bases, forces composition and tech trees, likely states of the overall game (including opponents' economies, structures spatial distributions).

From a macroeconomic perspective, one should understand concepts such as resource collection rates, convergence points in economic development for specific compositions, optimal responses to the economic actions of the opponents. From a micro-game perspective, students should find high value regions in the game (resources, defense perspectives, structures deployment), show creativity at tactical level (exploiting infrequent micro-game states).

It should be noted that there is also modern research into game theory and in using reinforcement learning (a machine learning technique in which artificially intelligent agents are the ones making decisions which are rewarded or punished) in order to improve AI
training systems for simulators or games.

In schools students should analyze such games at different complexity levels. Beginners (primary and middle school students) should learn the basics of playing games and finding optimal sequences of actions to actually win the games. Talent unveils early, and evaluating students and their native abilities can be automated: metrics include effective actions per minute, average time spent to provide moves, accuracy (including eye-hand coordination in RTS).

Ultimately a variety of non-common games are needed to not allow saturation between individual scores (on leaderboards): we must look for creativity and general abstract pattern recognition too in the individuals we evaluate.

The advantages of automatic student evaluation in these fields are clear: they are as bias-free as we currently can achieve, allowing students from any socio-economic background to demonstrate native and transferable skills. Those that will support technical and applicative sports while teaching students how to become competent decision makers will be those actually having a high caliber work force in the future.

Codrin Paul Oneci is a Romanian student studying aerospace engineering and physics at the Massachusetts Institute of Technology (MIT)

Guest Contributor

This piece was written for Greek City Times by a Guest Contributor