Chatterbot Essays

  • Chatterbot Observation

    784 Words  | 4 Pages

    There were external factors which I considered to ensure that we conduct the science experiment fairly. To keep it fair all variables, such as the; the questions, the response time, and the partner were all kept the same, except the change between the human and robot responses. First of all, when choosing partners, we chose people who we didn’t know well, so that we do not know too much detail about them and cannot relate it to there replies. As the speed of response could have an impact the time

  • John Searle's The Chinese Room Argument

    1040 Words  | 5 Pages

    The Chinese Room Argument was a thought experiment presented by an American philosopher by the name of John Searle. The Chinese room argument is a concept that refutes the idea of a strong artificial intelligence also known as Strong Al. Strong Ai is “the view that an appropriately programmed digital computer capable of passing the Turing test would thereby have mental states and a mind in the same sense in which human beings have mental states and a mind” (Searle, 2005). However the opposing view

  • Winograd Schhema Challenge Essay

    697 Words  | 3 Pages

    actually they have just been programmed with certain abilities, and they cannot extend beyond this, unlike us human, who can develop and extend their knowledge, and logic. Levesque’s basic theory behind this Winograd Schema Challenge, is testing the chatterbot by asking it a question that it is likely not to be familiar or programmed to have an answer to, and so it tests the chatterbot’s immediate response based on its pure intelligence. Lovesick published another sample question which displayed this

  • Cleverbot Response Paper

    585 Words  | 3 Pages

    This was one of the messages that I received from cleverbot, this shows how he has stored a response from a previous user, this is a strategy the robot uses to disguise itself, the capital ‘H’ shows that the the user has made a typo, using such responses instead of giving perfectly written answers, it blends in as a human. The second response shows how instead of being programmed to recognise the numerals and giving a correct answer, giving a random answer from the user can help it blend in more