In Daniel Dennett's 1995 book "Darwin's Dangerous Idea" he describes a concept he calls the Tower of Generate-and-Test. This is a kind of model of the evolution of intelligent agents.  A summary of the tower, starting from the bottom:  - Darwinian creatures - use natural selection as the generate and test mechanism.
 - Skinnerian creatures - can learn by simple reinforcement learning.
 - Popperian creatures - have a world model, can virtualize sense data and test actions under simulation.
 - Gregorian creatures - tool makers including language and culture.
 - Scientific creatures - Dennett proposes that the scientific method warrants a further floor of the tower.
 
- Walterian creatures - artificial, engineered creatures, named after W. Grey Walter, robot inventor.
 
If you consider the class of all optimisation processes, you get a rather different picture. Describing each stage in terms of what it adds to the previous level of the tower - and starting from the bottom:
- Stateless search - optimization with no memory - e.g.: random search.
 - Serial search - uses one agent - e.g.: Newton-Raphson.
 - Parallel search - uses multiple agents - e.g.: simulated-annealing.
 - Splitting - uses agents that can divide and reproduce - e.g.: a simple asexual genetic algorithm.
 - Merging - uses agents that can merge together - e.g. sexual reproduction and parasitism.
 - Learning - uses evolving agents that can additionally learn.
 - Virtualisation - uses agents that can perform most evaluations under simulation.
 - Culture - uses agents that have developed cultural transmission.
 - Artefact symbiosis - the memes start to build tools, minds and bodies for themselves.
 - Genetic engineering - the agents apply their tools to their own germ-line.
 - All-engineered - uses entirely engineered agents - e.g.: machine intelligence and robots.
 


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