Multi-species skill-evolution: stages and assumptions

Theory for the multi-layered evolution of skills in vertebrates, primarily in mammals

1. There are additional layers of simultaneous evolution for human skills.
   1. Symbolic communication embedded within writing for transport of the skill.
   • Encoding: the suggested behaviour is embedded within a story and framed by it
   • Examples: Ethical decision-making influenced by religion as carried by the Bible or the Torah, etc
   • Examples: Engineering design based on science that was conveyed by journal articles and books
   • Examples: Professional skills learnt from textbooks schooling, and online materials
   • Examples: Conducting military operations guided by military strategic instruction transported by courier or by code
   2. Computer-aided skills involving collaborations with computer data and simulations
   • Examples: Operators running chemical plants or manufacturing with process control
   The present research focuses on the first three layers, up to the beginnin of speech for humans.
2. Functionality is accrued over time and over successive generations, species, and layers. The sequence of first appearance of functionality is ordered in time and over species. Similarly, the sequence of first appearance of the layers is ordered over time and species. It is not implied, however, that evolution of lower layers ceases once higher layers are evolving.
3. The sequence of first appearance of functionality during evolution or maturation reflects functional dependencies. These functional dependencies are preserved during the execution of a skill to produce skilled behaviour.

Simple skilled behaviours that are simulated to investigate the layers from the perspective of evolution, i.e. the fitness-biased mechanisms that copy skills from one generation to the next.

1. Symbolic communication embedded within writing for transport of the skill.
• Examples to simulate (past): The use of written language to teach research design and analysis as tasks - (using TARA as illustration).
• Questions on the communication-learnt side:
• Questions on the writing side:
2. Computer-aided skills involving collaborations with computer data and simulations
• Examples to simulate (past):
• TARA - the use of computer-aided experiment-simulation to help students learn research design and analysis
• Expert systems, especially as used to capture and preserve the expertise that has been gained through years of experience and that cannot be passed on through an apprenticeship program
• Questions on the writing side:
• Questions on the use-of-computer side:

Simple skilled behaviours that are simulated to investigate the interaction between the functionality of the layers during human maturation, i.e. the process of developing from conception to adult:

1. Symbolic communication embedded within writing for transport of the skill.
• Examples to simulate: The use of written language to teach research design and analysis as tasks - (using TARA as illustration).
• Questions on the communication-learnt side:
• Questions on the writing side:
2. Computer-aided skills involving collaborations with computer data and simulations
• Examples to simulate: TARA - the use of computer-aided experiment-simulation to teach research design and analysis. Video games, collaborative work via the cloud.
• Questions on the writing side:
• Questions on the use-of-computer side:

The fundamental assumptions for the whole project:

1. Skills are self-assembled, i.e. without divine or other programmer
2. All skills rely on neural, dendrite, and synapse programming. They therefore use extremely slow processors Neuron run at 100Hz = 10ms, more than 10 million times slower than a PC, but use billions of processors in parallel compared to 4 or 8 for a PC.
3. Many skills are not inherited, i.e. programed by the genome. An example includes the ability to speak English and French. Such skills have been learnt after conception and birth.
4. Almost all skills have evolved, including learnt skills.
5. Innate and learnt skills have separate mechanisms for evolution.
6. Cooperation plays a role in the various mechanisms for evolution.
7. The functionality of skills accrues over evolution and maturation, i.e. later skills draw on earlier skills.

The framing assumptions for the whole project, separating skills from other components:

• Input from the world to skills comes through the perception system, primarily vision and hearing.
• All data from the perceptual analysis is available simultaneously as input to skills, somewhat like a buffet or smorgasbord.
• In some cases, skills and muscle action may be required for perception, such as for moving and focussing the eyes.
• Output to the world goes through action, through the motor-cortex, muscles controlling the angles of joints connecting limbs.
• Feedback controls may link perception to action without going through skills.
• A skeleton with 15 joints and 3 polar coordinates per joint is used for modeling locomotion.
• Joint angles are used instead of relative muscle-tension, to simplify the model
• Neurons are simplified.
• 25 frames per second equals 40 msec between frames, which is used as default neuron firing rate with a synchronized clock
• Numeric instead of binary values.

The basic stages and research questions for the whole project:

1. Innate skills for locomotion
• How the genome represents the programming for the skill, how it is combined from the parents, and how it evolves.
• How the neurons in the brain represent the skill
• How the functions to produce the skilled behaviour
2. Innate skill that are required for learning skills through the mimicry of skilled behaviour