Information Reduction

Combinatorial explosion

Objects and relations Let us first take a set of objects and consider how many connections (relations) there are between them, leaving aside the nature of the relationships and focussing solely upon their number. This is quite a simple task, because there is always exactly one relation between any two objects. Even if the two objects are entirely unrelated, this fact has a meaning and is thus useful information. We can count the number of possible connections between the objects and compare the number of objects with the number of possible relations. Fig 1: Seven objects and their relations Figure

By Hans Rudolf Straub|2025-11-25T18:16:32+00:0016. March 2020|Categories: Artificial Intelligence, Information, Logic, Logodynamics, Information Reduction|Tags: Combinatorial Explosion|0 Comments

Information Reduction 7: Micro and Macro State

Examples of information reduction In previous texts we looked at examples of information reduction in the following areas: Coding / classification Sensory perception DRG (Flat rate per case) Opinion formation Thermodynamics What do they have in common? Micro and macro state What all these examples have in common is that, in terms of information, there are two states: a micro state with a great many details and a macro state with much less information. One very clear example that many of us will remember from our school days is the relationship between the two levels in thermodynamics. The two states

By Hans Rudolf Straub|2025-11-15T13:22:25+00:0013. January 2020|Categories: Information, Entropy, Information Reduction, Micro / Macro|Tags: Information Reduction, Macro State, Micro State|0 Comments

Information Reduction 6: The Waterglass, Revisited

Is that physics? In my article Information reduction 5: The classic glass of water, I drew upon the example of a glass of water to illustrate the principle of information reduction. In this example, the complex and detailed information about the kinetic energy of water molecules (micro level) is reduced to simple information about the temperature of the water. Of course, a physicist might criticise this example – and quite rightly so, because the glass of water is actually much more complicated than this. Boltzmann’s calculations only apply to the ideal gas, i.e. one whose molecules do not interact except

By Hans Rudolf Straub|2025-11-15T13:22:51+00:0012. January 2020|Categories: Information, Information Reduction|Tags: Information Reduction|0 Comments

Information Reduction 5: The Classic Glass of Water

Information reduction in thermodynamics A very specific example of information reduction can be found in the field of thermodynamics. What makes this example so special is its simplicity. It clearly illustrates the basic structure of information reduction without the complexity found in other examples, such as those from biology. And it’s a subject many of us will already be familiar with from our physics lessons at school. What is temperature? A glass of water contains a huge amount of water molecules, all moving at different speeds and in different directions. These continuously collide with other water molecules, and their speed

By Hans Rudolf Straub|2025-11-15T13:24:59+00:0011. June 2019|Categories: Information, Entropy, Information Reduction, Micro / Macro|Tags: Information Reduction, Information Theory, Ludwig Boltzmann, Macro Level, Micro Level, Thermodynamics|0 Comments

Information Reduction 4: Framing

Framing matters The framing effect is a topic that comes up a lot these days. Framing is the phenomenon whereby the same message is perceived differently, depending on what additional information is sent with it. The additional information is provided to give the message the right ‘frame’ so that recipients respond appropriately. Even if the additional information is undoubtedly true, the recipient can be genuinely manipulated by framing, simply by the selection of details that are in themselves factually correct. Framing is, of course, used in advertising, but its role in political reporting has become something of a hot topic

By Hans Rudolf Straub|2025-11-15T13:25:30+00:0011. June 2019|Categories: Information, Information Reduction|Tags: Information Reduction, Information Selection|0 Comments

Information Reduction 3: Information is Selection

Information reduction is everywhere In a previous post, I described how the coding of medical facts – a process that leads from a real-world situation to a flat rate per case (DRG) – involves a dramatic reduction in the amount of information: Information reduction This information reduction is a very general phenomenon and by no means limited to information and its coding in the field of medicine. Whenever we notice something, our sensory organs – for example our retinas – reduce the amount of information we take in. Our brain then simplifies the data further so that only the essence

By Hans Rudolf Straub|2025-11-15T13:25:53+00:0011. June 2019|Categories: Information, Information Reduction|Tags: Health Care, Information Reduction, Information Selection, Information Theory, Medicine|0 Comments

Information Reduction 2: The Funnel

The funnel of information reduction In my previous article Information reduction 1, I described a chain of information processing from the patient to the flat rate per case (DRG): This acts as a funnel, reducing the amount of information available at each step. The extent of the reduction is dramatic. Imagine we have the patient in front of us. One aspect of a comprehensive description of this patient is their red blood cells. There are 24-30 trillion (= 24–30·1012 ) red blood cells in the human body, each with a particular shape and location in the body, and each moving in

By Hans Rudolf Straub|2025-11-15T13:26:57+00:0011. June 2019|Categories: Information, Entropy, Information Reduction, Micro / Macro|Tags: funnel, Health Care, ICD-10, Information Reduction|0 Comments

Information Reduction 1: Coding

Two types of coding In a previous post, I described two fundamentally different types of coding. In the first, the intention is to carry all the information contained in the source over into the encoded version. In the second, on the other hand, we deliberately refrain from doing this. It is the second – the information-losing – type that is of particular interest to us. When I highlighted this difference in my presentations twenty years ago and the phrase ‘information reduction’ appeared prominently in my slides, my project partners pointed out that this might not go down too well with