TAILIEUCHUNG - Robot Learning 2010 Part 2

Tham khảo tài liệu 'robot learning 2010 part 2', kỹ thuật - công nghệ, cơ khí - chế tạo máy phục vụ nhu cầu học tập, nghiên cứu và làm việc hiệu quả | 8 Robot Learning Q st at Q st at a rt i Y max Q st 1 a - Q st at 3 5. Some existing LCSs for robotics LCSs were invented by Holland Holland 1975 in order to model the emergence of cognition based on adaptive mechanisms. They consist of a set of rules called classifiers combined with adaptive mechanisms in charge of evolving the population of rules. The initial goal was to solve problems of interaction with an environment such as the one presented in figure 2 as was described by Wilson as the Animat problem Wilson 1985 . In the context of the initial research on LCSs the emphasis was put on parallelism in the architecture and evolutionary processes that let it adapt at any time to the variations of the environment Golberg Holland 1988 . This approach was seen as a way of escaping brittleness Holland 1986 in reference to the lack of robustness of traditional artificial intelligence systems faced with problems more complex than toy or closed-world problems. Pittsburgh versus Michigan This period of research on LCSs was structured by the controversy between the so-called Pittsburgh and Michigan approaches. In Smith s approach Smith 1980 from the University of Pittsburgh the only adaptive process was a GA applied to a population of LCSs in order to choose from among this population the fittest LCS for a given problem. By contrast in the systems from Holland and his PhD students at the University of Michigan the GA was combined since the very beginning with an RL mechanism and was applied more subtly within a single LCS the population being represented by the set of classifiers in this system. Though the Pittsburgh approach is becoming more popular again currently Llora Garrell 2002 Bacardit Garrell 2003 Landau et al. 2005 the Michigan approach quickly became the standard LCS framework the Pittsburgh approach becoming absorbed into the wider evolutionary computation research domain. The ANIMAT classifier system Inspired by Booker s two-dimensional critter Wilson

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