Editing Logic programming (section)

===Relationship with the [[Computational-representational understanding of mind]]===

In his popular Introduction to Cognitive Science,<ref>{{Cite book|title=Mind: Introduction to Cognitive Science|last=Thagard|first=Paul|publisher=The MIT Press|year=2005|isbn=9780262701099|pages=11}}https://www.google.co.uk/books/edition/Mind_second_edition/gjcR1U2HT7kC?hl=en&gbpv=1&pg=PP11&printsec=frontcover</ref> [[Paul Thagard]] includes logic and [[Rule-based system|rules]] as alternative approaches to modelling human thinking. He argues that rules, which have the form ''IF condition THEN action'', are "very similar" to logical conditionals, but they are simpler and have greater psychological plausibility (page 51). Among other differences between logic and rules, he argues that logic uses deduction, but rules use search (page 45) and can be used to reason either forward or backward (page 47). Sentences in logic "have to be interpreted as ''universally true''", but rules can be ''defaults'', which admit exceptions (page 44).

He states that "unlike logic, rule-based systems can also easily represent strategic information
about what to do" (page 45). For example, "IF you want to go home for the weekend, and you have bus fare, THEN
you can catch a bus". He does not observe that the same strategy of reducing a goal to subgoals can be interpreted, in the manner of logic programming, as applying backward reasoning to a logical conditional:

<syntaxhighlight lang="prolog">
can_go(you, home) :- have(you, bus_fare), catch(you, bus).
</syntaxhighlight>

All of these characteristics of rule-based systems - search, forward and backward reasoning, default reasoning, and goal-reduction - are also defining characteristics of logic programming. This suggests that Thagard's conclusion (page 56) that:

<blockquote>
Much of human knowledge is naturally described in terms of rules, and many kinds of thinking such as planning can be modeled by rule-based systems.
</blockquote>
also applies to logic programming.

Other arguments showing how logic programming can be used to model aspects of human thinking are presented by [[Keith Stenning]] and [[Michiel van Lambalgen]] in their book,
Human Reasoning and Cognitive Science.<ref>{{cite book
  | last = Stenning
  | first = Keith
  |author2=van Lambalgen, Michiel
  | title = Human reasoning and cognitive science
  | url = https://archive.org/details/humanreasoni_sten_2008_000_10735669
  | url-access = registration
  | publisher = [[MIT Press]]
  | year = 2008| isbn = 978-0-262-19583-6
 }}https://philpapers.org/archive/STEHRA-5.pdf</ref> They show how the non-monotonic character of logic programs can be used to explain human performance on a variety of psychological tasks. They also show (page 237) that  "closed–world reasoning in its guise as logic programming has an appealing neural implementation, unlike classical logic."
  
In The Proper Treatment of Events,<ref>Van Lambalgen, M. and Hamm, F., 2008. The proper treatment of events. John Wiley & Sons.
https://citeseerx.ist.psu.edu/document?repid=rep1&type=pdf&doi=3126320bb6e37ca3727fed404828b53fc56ff063</ref>
Michiel van Lambalgen and Fritz Hamm investigate the use of constraint logic programming to code "temporal notions in natural language by looking at the way human beings construct time".