Required definitions                                           : All four options, with reference to the problem.

Research Topic 0 (background)                         : Plato, Simple Heuristics That Make Us Smart

Research Topic 1 (introduction)                        : Davild Hilbert, the Church-Turing thesis

Research Topic 2 (current debates) : Hubert Dreyfus on embodied cognition

Research Topic 3 (sophistication)                     : What is a decision?

 

Short answer        : It is more correct to say that he has come to a conclusion –a claim based on executive selection across available processing modules and styles. He used developed faculties in all four to arrive at this conclusion.It’s important to remember that categories of decision and logic are explicative rather than formative; that is, they explain individual events to us, rather than actually mapping/ describing the event.

All this being said, there are examples below of the solution as each option.

 

Analogy                  :When you last ate, was it because it was convenient, because you had time, because you were hungry, for comfort, or some combination of the four?

 

Problems               : The actual answer is either e) all of the above, since albert’s actual analysis will be synthetic across available processing modules and styles; he will use each of the above as much as they can be, given his ability. The classes defined are approaches to describing decision making; actual decision making is itself a distributed task. The decision he made can be classed as each of these as follows:

 

Syllogism.

Premiss 1:             (All known) Members of my family left high school.

Premiss 2:             I am a member of my family.

Conclusion:           I will leave high school.

Technically, though, this isn’t a valid syllogism because the premises make an incorrect logical assumption; that all known instances describe all possible instances (improper induction)

 

Availability heuristic

An availability heuristic is a kind of syllogism based on suboptimal data – instances at hand rather than all possible instances (as above).

Education is precluded in my socioeconomic environment. Albert has made a calculation concerning the availability of education to him, given the socioeconomic environment his family lives in. For instance, if his family members all dropped out because of needing to get jobs, then he has a valid availability heuristic.

 

Algorithm

An algorithm is any logical sequence of well-defined instructions. This makes it a chain of valid syllogisms. (unlike the two examples above, which are short chains of invalid logical moves). It also has to end; consider flow charts, computer operations, etc., etc.

In this case, it would go something like this;

 

Means-end analysis

If albert’s goal state, in common with his parents and brother, includes no need for school beyond the eighth grade – if his family are all carpenters, for example – then his goal state has determined his analysis.

 

Sophistication       :Albert’s decision could also be mapped by Bayes theorem, which is extremely controversial because it is the ultimate black box; JoshuaTenenbaum work onmodelling causal reasoning and grammars, for example, produce far better decision modelling than virtually all other machine learning systems, but does so at the cost of any explicability in any but the most statistical, correlative manner (which would be abominable, if it wasn’t right all the time, much like quantum mechanics). ; every outcome is simply the consequence of a single prior probability rather than a distinct logical chain.

 

References            :

Craver, C.F., 2007. Explaining the Brain: Mechanisms and the Mosaic Unity of Neuroscience, Oxford University Press.

Wolpert, D.H., (1996) The lack of a priori distinctions between learning algorithms, Neural Computation archive, Volume 8 ,  Issue 7

Velmans, Max (1991) Is Human Information Processing Conscious?  Behavioral and Brain Sciences, 14, 651-726.

Gigerenzer,G., Todd, P. M., ABC Research Group, 2000, Simple Heuristics That Make Us Smart, Oxford: Oxford University Press.

John  Haugeland, Artificial  Intelligence  80  (1996)  119-128, Body  and  world:  a  review  of  What  Computers Still Can’t  Do:  A  Critique  of  Artificial Reason (by Hubert  L.  Dreyfus)