Multistrategy Learning Methods for Multirobot Systems

نویسندگان

  • R. C. Arkin
  • Y. Endo
  • B. Lee
  • E. Martinson
چکیده

This article describes three different methods for introducing machine learning into a hybrid deliberative/reactive architecture for multirobot systems: learning momentum, Q-learning, and CBR wizards. A range of simulation experiments and results are reported using the Georgia Tech MissionLab mission specification system.

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

منابع مشابه

Pluto: Managing Multistrategy Learning through Planning

Multistrategy learning systems are systems that employ multiple methods to solve learning problems. In many multistrategy systems, either the user or the system selects a single method to use on the current problem. At best, such a selection-type multistrategy learning system can solve the union of the problems solvable by the individual learning methods it contains. Another strategy is to have...

متن کامل

Crucial Factors in Cooperative Multirobot Learning

Cooperative decentralized multirobot learning refers to the use of multiple learning entities to learn optimal solutions for an overall multirobot system. We demonstrate that traditional single-robot learning theory can be successfully used with multirobot systems, but only under certain conditions. The success and the effectiveness of single-robot learning algorithms in multirobot systems are ...

متن کامل

Appears in Machine Learning: A Multistrategy Appraoch, Vol. IV

This chapter describes a multistrategy system that employs independent modules for deductive, abductive, and inductive reasoning to revise an arbitrarily incorrect propositional Horn-clause domain theory to t a set of preclassi ed training instances. By combining such diverse methods, Either is able to handle a wider range of imperfect theories than other theory revision systems while guarantee...

متن کامل

Crucial factors affecting cooperative multirobot learning

Cooperative decentralized multirobot learning refers to the use of multiple learning entities to learn optimal solutions for an overall multirobot system. We demonstrate that traditional single-robot learning theory can be successfully used with multirobot systems, but only under certain conditions. The success and the effectiveness of single-robot learning algorithms in multirobot systems are ...

متن کامل

An Empirical Study of Computational Introspection: Evaluating Introspective Multistrategy Learning in the Meta-AQUA Syste

The theory of introspective multistrategy learning proposes that three transformations must occur to learn effectively from a performance failure in an intelfigent system: Blame assignment, deciding what to learn, and learning-strategy construction. The Meta-AQUA system is a multistrategy learner that operates in the domain of story-understanding failures and is designed to evaluate this learni...

متن کامل

ذخیره در منابع من


  با ذخیره ی این منبع در منابع من، دسترسی به آن را برای استفاده های بعدی آسان تر کنید

برای دانلود متن کامل این مقاله و بیش از 32 میلیون مقاله دیگر ابتدا ثبت نام کنید

ثبت نام

اگر عضو سایت هستید لطفا وارد حساب کاربری خود شوید

عنوان ژورنال:

دوره   شماره 

صفحات  -

تاریخ انتشار 2003