Category: Internal Senses
Posted on January 3, 2021
Coherency and the Game Combos
In statistics, one learns very early on that independent random variations tend to cancel out when grouped together. By the law of large numbers, the collective behavior of many independent random entities tends to closely reflect the average behavior of these entities. This is very convenient if we see the random variations as being meaningless noise and were only interested in the average. But if the variations contained all the interesting complexity, then the complexity is washed away in the aggregate. In a generic society, the generics may be highly varied and individually very complex. Naively put them in a group and the collective behavior is simpler – quite plausibly, the variations cancel toward zero and the group achieves nothing as a whole.
This all changes if the random variations were not independent and tended to align along certain dimensions. The variations will be amplified wherever they align, and the collective behavior of the group cleanly emphasizes the alignment of its constituents. If we want a group of generics to retain a meaningful identity distinct from the average of its members, we need to give the generics a desire to align with each other in behavior or motivation. The topic of today’s post is the coherency domain, which contains ideas that lend well to being mixed with other constructs to describe nontrivial social behaviors. As an example, I will use concepts from the coherency domain to describe the gaming combos, which are a set of methods for creating alignment even between unrelated or mutually exclusive activities through the common participation of a bigger event.
Updated on January 3, 2021
The OpenSense Domain
Communication is essential in allowing individuals to cooperate in group activity, especially if the individuals differ in their roles or characteristics. Having open access to information greatly boosts the productivity of a group – in fact, this is the motivating principle behind the invention of patents, the internet, and open source software. Similarly, members of a team are expected to openly share their thoughts and tendencies so that the team can make up for each other’s weaknesses. In the OpenSense
domain, we discuss what happens when important facets of generic thought are openly expressed and easily sensed by others in the environment. We will talk about how generics in this domain tend to form friendship groups, share information about themselves, and engage in play activities designed to uncover highly varied aspects of each other’s personalities. The senses in this domain are analogous to human emotions and the involuntary facial expressions / body language used to express such emotions1, but in this post I will mostly focus on the OpenSense
dynamics in its pure form and only use human behaviors as illustrative examples.
Posted on October 14, 2020
The Rivalry Domain
Previously, I’ve been talking in broad terms about very general concepts in proficiology. This will be the first time I narrow my focus into a specific domain. A domain is a restricted setting with only a small number of relevant events / senses / agents – basically a toy problem, or a simplified model environment. The hope is that we can use important ideas from these domains as fundamental building blocks that will help us analyze more complex setups. In other words, we should be able to build more interesting / realistic generics by mixing & matching simple components from multiple domains, as if we were building a complex molecule atom-by-atom.
In this post we will talk about the Rivalry
domain, which focuses on events where one generic benefits at another generic’s loss. I will supplement my explanation with formal notation loosely based on functional programming languages. I am not requiring (or expecting) readers to have a background in computer science – it’s just that this kind of notation is very useful for describing nontrivial generic behaviors through the composition of simpler constructs. In any case, I will be explaining this functional notation as I go.