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Launching Into AI's October Sky with Robotics and Lisp

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Launching Into AI's October Sky with Robotics and Lisp AI Magazine Volume 27 Number 1 (2006) (© AAAI) Articles Launching into AI’s October Sky with Robotics and Lisp Frank Klassner ■ Robotics projects coupled with agent-oriented 1960s. Look at what today’s undergraduates are trends in artificial intelligence education have the seeing and hearing about AI in popular culture. potential to make introductory AI courses at liberal Besides the popularity of the AI-inspired fiction arts schools the gateway for a large new generation in the movies I, Robot and A.I., consider the of AI practitioners. However, this vision’s achieve- highly publicized success of the Mars rovers ment requires programming libraries and low-cost Spirit and Opportunity, the ESPN coverage of the platforms that are readily accessible to undergrad- uates and easily maintainable by instructors at sites DARPA autonomous vehicle Grand Challenge, with few dedicated resources. This article presents the lust among gamers after cleverer computer and evaluates one contribution toward imple- opponents, and the prevalence of word proces- menting this vision: the RCXLisp library. The li- sor speech-recognition systems. Students are brary was designed to support programming of the not just hearing about AI applications—they Lego Mindstorms platform in AI courses with the are experiencing them more directly than did goal of using introductory robotics to motivate un- the students in October Sky gazing up at Sput- dergraduates’ understanding of AI concepts within nik’s starlike dot. Today’s college and high the agent-design paradigm. The library’s evalua- school students can evaluate AI applications tion reflects four years of student feedback on its use in a liberal-arts AI course whose audience cov- firsthand (for example, in games, robotic vacu- ers a wide variety of majors. To help establish a um cleaners, and intelligent search engines). context for judging RCXLisp’s effectiveness this ar- More importantly for AI, the immediacy of ticle also provides a sketch of the Mindstorms- their experience often makes them feel they based laboratory in which the library is used. could replicate or even improve the applica- tions’ capabilities—if only they understood the AI theory behind the application. And this situation definitely is enticing stu- n the movie October Sky, a group of high dents into trying out introductory AI courses at school students become inspired to learn liberal arts colleges. The difficulty for instruc- Ihow to build high-altitude rockets after tors at such schools is retaining these students’ watching Sputnik glide across the night sky interest in the field after their first exposure to soon after it was launched in October 1957. To- formal AI. In many smaller schools’ computer day AI should be poised to capture students’ in- science departments there is at most one facul- terest and imaginations in the same way that ty member with AI training, usually with few movie showed one application in physics and dedicated resources. Instructors from such astronomy capturing them in the 1950s and schools have attested at AAAI and SIGCSE sym- Copyright © 2006, American Association for Artificial Intelligence. All rights reserved. 0738-4602-2006 / $2.00 SPRING 2006 51 Articles posia that they must tread carefully between a ficiencies can supply partial source code for AI breadth-first survey style that downplays full systems (like planners or search algorithms) for system implementation experience and a students to complete. Those who want to en- depth-first concentration on subfields that courage students’ deeper understanding of a might not directly relate to popular applica- topic through attention on “knob-turning” ex- tions without exorbitant software or hardware periments (Cohen 1995) can supply completed investments. A heavily unbalanced course, in source code sets from the same corpus. either direction, can leave undergraduates with All three trends have strongly influenced the unrealistic (or worse—nonexistent) views of AI curriculum at Villanova University. In the how real-world AI systems can be designed and fall of 1997 the introduction to AI course CSC implemented to meet real-world performance 4500 was reorganized around the concept of goals. agent-oriented design. This approach was aug- Fortunately, three trends are helping to mented in the fall of 1999, offering with team- maintain the balance that AI education needs based Lego Mindstorms (Klassner 2002) pro- for inspiring students from smaller schools. jects in order to have students explore the The first is the growth of the intelligent agent relationships among hardware, environment, design framework (Russell and Norvig 2003) and software organization in agent design. that emphasizes study of the limits and capa- Since the spring 2001 course we have used the bilities of different AI techniques in producing RCXLisp library developed at Villanova for pro- actions appropriate to an agent’s environment. gramming Mindstorms in Common Lisp. This Because it stresses identification of the weak- article describes the RCXLisp library with re- nesses as well as the strengths of these tech- spect to these trends, focusing on its develop- niques, this framework also naturally encour- ment, its uses in CSC 4500, and student feed- ages exploration of how to integrate two or back on both the course and its library. To help more AI techniques (as might be covered in a the reader evaluate RCXLisp’s effectiveness, more breadth-first oriented course) into hybrid this article also provides a sketch of the Mind- systems so as to mitigate their individual weak- storms-based laboratory in which the library is nesses. used. The second trend is the increasing availabil- ity of low-cost robotics platforms1 that can play the same motivating role in AI education that Choosing Mindstorms and Lisp model rockets and toy telescopes did for as- The CSC 4500 course is an elective with no for- tronomy and physics education in the past mal programming prerequisites. Computer sci- century. Pure software-oriented projects such as ence majors typically take the course in their gaming agents or simulations can indeed moti- fourth year, by which time most of these stu- vate students, but there is no denying the in- dents have taken a programming languages creased registration levels seen in elective AI course that introduces them to Lisp. The course courses the first time a new robot-development is also open to third- and fourth-year cognitive component is announced for them. science concentrators and computer engineer- The third trend is vital to the success of the ing majors, who generally have no program- second. It is the growing body of open-source ming experience in Lisp and as little as one se- software systems and programming tools for mester of introductory programming in Java robot kits that allows students with limited re- from their first year. The cognitive science stu- sources to move quickly from learning about AI dents hail from a variety of majors: biology, po- techniques in the abstract to actually building litical science, and physics, to name a few. artifacts with them (Yuasa 2003).2 It is not The course uses Common Lisp in its pro- enough to give students a robot platform that gramming projects for two reasons. The first is requires a whole semester to learn how to pro- to leverage Lisp’s support for rapid prototyping gram. After installing the platform’s program- against the large body of open-source AI Lisp ming tools, students should be able to get past systems. The second is to reinforce computer “Hello Robot” trials quickly in order to grapple science majors’ Lisp experience from their pro- with moderately complex programs with con- gramming languages course, thereby offering fidence-boosting results. From a small-college students another option besides C/C++ for instructors’ perspective, the most effective ele- meeting the department goal that graduates be ments in this software collection allow them to familiar with at least one language beyond Ja- extend the depth of their courses’ coverage in va. various ways. Those instructors who want to Once the decision was made in 1997 to orga- encourage students’ deeper understanding of a nize CSC 4500 around the agent paradigm, as- topic through attention to implementation ef- signments using robotic agent simulations 52 AI MAGAZINE Articles were tried but did not generate significant en- thusiasm among students. Based on student feedback and positive reports on robots’ use in Infrared (IR) Tower the computer science education literature (Beer, Chiel, and Drushel 1999; Kumar and Effector Meeden 1998; Mazur and Kuhrt 1997; and Ports Stein 1996), the decision was made to try using LCD physical robots in the course. The choice of ro- Display bot platform was based on four criteria: pro- gramming environment, cost, flexibility, and “student comfort level.” In 1999 there was no low-cost robot kit that supported Common Lisp programming, so this criterion played a negligible role in the decision. A Mindstorms kit with 750 construction pieces, sensors, and programmable hardware cost approximately Sensor US$200. This was one quarter the cost of some IR Port Handy Board–based robot kits and one tenth Ports the cost of an ActivMedia-based robot kit—two of the other platforms considered. In the time since this evaluation was conducted Lego has Figure 1. The Lego Mindstorms Infrared released a “RoboChallenge” kit for US$150 that Transceiver Tower (Left) and the RCX Unit (Right). has fewer construction pieces (250) for courses where a sophisticated robot chassis is unneces- sary. In terms of flexibility the Mindstorms kit guages distracted students from learning the AI supports the creation of effectors such as arms, concepts of the course. We also found the lan- grippers, legs, tread casings, and so on, often guage had little support for coordinating teams not available in other basic kits. The Handy of robots, though this problem is due more to Board platform, however, was similarly exten- NQC’s dependence on Lego’s firmware than to sible.
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