Learning action strategies for planning domains
نویسندگان
چکیده
منابع مشابه
Learning Action Strategies for Planning Domains Learning Action Strategies for Planning Domains
This paper reports on experiments where techniques of supervised machine learning are applied to the problem of planning. The input to the learning algorithm is composed of a description of a planning domain, planning problems in this domain, and solutions for them. The output is an eecient algorithm | a strategy | for solving problems in that domain. We test the strategy on an independent set ...
متن کاملLearning Action Strategies for Planning Domains
This paper reports on experiments where techniques of supervised machine learning are applied to the problem of planning. The input to the learning algorithm is composed of a description of a planning domain, planning problems in this domain, and solutions for them. The output is an eecient algorithm | a strategy | for solving problems in that domain. We test the strategy on an independent set ...
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There are many different approaches to solving planning problems, one of which is the use of domain specific control knowledge to help guide a domain independent search algorithm. This paper presents L2Plan which represents this control knowledge as an ordered set of control rules, called a policy, and learns using genetic programming. The genetic program’s crossover and mutation operators are ...
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We present a planning system for selecting policies in probabilistic planning domains. Our system is based on a variant of approximate policy iteration that combines inductive machine learning and simulation to perform policy improvement. Given a planning domain, the system iteratively improves the best policy found so far until no more improvement is observed or a time limit is exceeded. Thoug...
متن کاملLearning Measures of Progress for Planning Domains
We study an approach to learning heuristics for planning domains from example solutions. There has been little work on learning heuristics for the types of domains used in deterministic and stochastic planning competitions. Perhaps one reason for this is the challenge of providing a compact heuristic language that facilitates learning. Here we introduce a new representation for heuristics based...
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ژورنال
عنوان ژورنال: Artificial Intelligence
سال: 1999
ISSN: 0004-3702
DOI: 10.1016/s0004-3702(99)00060-0