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- Action_model_learning abstract "Action model learning (sometimes abbreviated action learning) is an area of machine learning concerned with creation and modification of software agent's knowledge about effects and preconditions of the actions that can be executed within its environment. This knowledge is usually represented in logic-based action description language and used as the input for automated planners. Learning action models is important when goals change. When an agent acted for a while, it can use its accumulated knowledge about actions in the domain to make better decisions. Thus, learning action models differs from reinforcement learning. It enables reasoning about actions instead of expensive trials in the world.Action model learning is a form of inductive reasoning, where new knowledge is generated based on agent's observations. It differs from standard supervised learning in that correct input/output pairs are never presented, nor imprecise action models explicitly corrected.Usual motivation for action model learning is the fact that manual specification of action models for planners is often a difficult, time consuming, and error-prone task (especially in complex environments).".
- Action_model_learning wikiPageID "43808044".
- Action_model_learning wikiPageLength "7268".
- Action_model_learning wikiPageOutDegree "34".
- Action_model_learning wikiPageRevisionID "642592154".
- Action_model_learning wikiPageWikiLink Action_language.
- Action_model_learning wikiPageWikiLink Answer_set_programming.
- Action_model_learning wikiPageWikiLink Architecture_description_language.
- Action_model_learning wikiPageWikiLink Artificial_intelligence.
- Action_model_learning wikiPageWikiLink Automated_planning_and_scheduling.
- Action_model_learning wikiPageWikiLink Boolean_satisfiability_problem.
- Action_model_learning wikiPageWikiLink Category:Data_mining.
- Action_model_learning wikiPageWikiLink Category:Inductive_reasoning.
- Action_model_learning wikiPageWikiLink Category:Machine_learning.
- Action_model_learning wikiPageWikiLink Computational_logic.
- Action_model_learning wikiPageWikiLink Greedy_algorithm.
- Action_model_learning wikiPageWikiLink Inductive_logic_programming.
- Action_model_learning wikiPageWikiLink Inductive_reasoning.
- Action_model_learning wikiPageWikiLink Knowledge_representation_and_reasoning.
- Action_model_learning wikiPageWikiLink Machine_learning.
- Action_model_learning wikiPageWikiLink Maximum_satisfiability_problem.
- Action_model_learning wikiPageWikiLink Perceptron.
- Action_model_learning wikiPageWikiLink Planning_Domain_Definition_Language.
- Action_model_learning wikiPageWikiLink Reinforcement_learning.
- Action_model_learning wikiPageWikiLink STRIPS.
- Action_model_learning wikiPageWikiLink Software_agent.
- Action_model_learning wikiPageWikiLink Supervised_learning.
- Action_model_learning wikiPageWikiLink Test_set.
- Action_model_learning wikiPageUsesTemplate Template:Machine_learning_bar.
- Action_model_learning wikiPageUsesTemplate Template:Reflist.
- Action_model_learning subject Category:Data_mining.
- Action_model_learning subject Category:Inductive_reasoning.
- Action_model_learning subject Category:Machine_learning.
- Action_model_learning hypernym Area.
- Action_model_learning type Place.
- Action_model_learning comment "Action model learning (sometimes abbreviated action learning) is an area of machine learning concerned with creation and modification of software agent's knowledge about effects and preconditions of the actions that can be executed within its environment. This knowledge is usually represented in logic-based action description language and used as the input for automated planners. Learning action models is important when goals change.".
- Action_model_learning label "Action model learning".
- Action_model_learning sameAs m.0127g7vy.
- Action_model_learning wasDerivedFrom Action_model_learning?oldid=642592154.
- Action_model_learning isPrimaryTopicOf Action_model_learning.