Artificial intelligence aims to mimic the `operation' of the human mind using sequential machines, automata, robots, or computers. Indeed there are two different claims on how far AI can go in exhibiting human behaviors, and especially in emulating the actions of the human mind:

• Strong AI thesis, or `general intelligence', is a very long term aim of AI research in Computer Science that might not be achievable within the bounds of Boolean logic if it does aim to match human intelligence that often operates beyond chrysippian, formal or even symbolic two-value logic, and indeed as it remains currently undefined (or undefinable ?) in terms of either Boolean or symbolic, two-value logic.
  
• Weak AI thesis:
  1. Knowledge-based AI
  2. Symbolic computation AI
  3. Sub-symbolic AI
  4. Computational `Intelligence' and `Neural' Networks or Nets

Remarks:

1. A Super-complex Computer System Architecture may give one the illusion of `strong AI' in spite of its Boolean logic limitations, as there are no stringent tests defined so far that are capable of correctly `measuring' intelligence either in humans or in computers. Until a satisfactory definition of `human intelligence' is arrived at, it will not be possible to design acceptable means or tests to `measure' such intelligence, and therefore one could not establish if the `strong AI' thesis is valid or not. It may indeed remain an undecidable issue on a chrysippian logic basis.
2. An universal Turing machine ($AUTM$ ) was shown to be able to simulate any other sequential machine, automaton, robot, or computer by employing steps that humans do not consider to require `intelligence' (i.e., human intelligence).