Entry Kumar:1998:RLT from sigcse1990.bib

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BibTeX entry

@Article{Kumar:1998:RLT,
  author =       "Deepak Kumar and Lisa Meeden",
  title =        "A robot laboratory for teaching artificial
                 intelligence",
  journal =      j-SIGCSE,
  volume =       "30",
  number =       "1",
  pages =        "341--344",
  month =        mar,
  year =         "1998",
  CODEN =        "SIGSD3",
  DOI =          "https://doi.org/10.1145/274790.274326",
  ISSN =         "0097-8418 (print), 2331-3927 (electronic)",
  ISSN-L =       "0097-8418",
  bibdate =      "Sat Nov 17 16:56:29 MST 2012",
  bibsource =    "http://portal.acm.org/;
                 http://www.math.utah.edu/pub/tex/bib/sigcse1990.bib",
  abstract =     "There is a growing consensus among computer science
                 faculty that it is quite difficult to teach the
                 introductory course on Artificial Intelligence well [4,
                 6]. In part this is because AI lacks a unified
                 methodology, overlaps with many other disciplines, and
                 involves a wide range of skills from very applied to
                 quite formal. In the funded project described here we
                 have addressed these problems by ``Offering a unifying
                 theme that draws together the disparate topics of AI;''
                 Focusing the course syllabus on the role AI plays in
                 the core computer science curriculum; and ``Motivating
                 the students to learn by using concrete, hands-on
                 laboratory exercises. Our approach is to conceive of
                 topics in AI as robotics tasks. In the laboratory,
                 students build their own robots and program them to
                 accomplish the tasks. By constructing a physical entity
                 in conjunction with the code to control it, students
                 have a unique opportunity to directly tackle many
                 central issues of computer science including the
                 interaction between hardware and software, space
                 complexity in terms of the memory limitations of the
                 robot's controller, and time complexity in terms of the
                 speed of the robot's action decisions. More
                 importantly, the robot theme provides a strong
                 incentive towards learning because students want to see
                 their inventions succeed. This robot-centered approach
                 is an extension of the agent-centered approach adopted
                 by Russell and Norvig in their recent text book [11].
                 Taking the agent perspective, the problem of AI is seen
                 as describing and building agents that receive
                 perceptions as input and then output appropriate
                 actions based on them. As a result the study of AI
                 centers around how best to implement this mapping from
                 perceptions to actions. The robot perspective takes
                 this approach one step further; rather than studying
                 software agents in a simulated environment, we embed
                 physical agents in the real world. This adds a
                 dimension of complexity as well as excitement to the AI
                 course. The complexity has to do with additional
                 demands of learning robot building techniques but can
                 be overcome by the introduction of kits that are easy
                 to assemble. Additionally, they are lightweight,
                 inexpensive to maintain, programmable through the
                 standard interfaces provided on most computers, and
                 yet, offer sufficient extensibility to create and
                 experiment with a wide range of agent behaviors. At the
                 same time, using robots also leads the students to an
                 important conclusion about scalability: the real world
                 is very different from a simulated world, which has
                 been a long standing criticism of many well-known AI
                 techniques. We proposed a plan to develop identical
                 robot building laboratories at both Bryn Mawr and
                 Swarthmore Colleges that would allow us to integrate
                 the construction of robots into our introductory AI
                 courses. Furthermore, we hoped that these laboratories
                 would encourage our undergraduate students to pursue
                 honors theses and research projects dealing with the
                 building of physical agents.",
  acknowledgement = ack-nhfb,
  fjournal =     "SIGCSE Bulletin (ACM Special Interest Group on
                 Computer Science Education)",
  journal-URL =  "http://portal.acm.org/browse_dl.cfm?idx=J688",
}

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