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1	Learning Partial Policies for Intractable Domains on Tractable Subsets. / Lärande av ofullständiga strategier för svårlärda domäner via lättlärda delmängder. Carlsson, Viktor January 2023 (has links) The field of classical planning deals with designing algorithms for generating plans or squences of actions that achieve specific goals. It involves representing a problem domain as a set of state variables, actions and goals, and then developing search algorithms that can explore the state of possible plans to find the one that satisfies the specified goal. Classical planning domains are often NP-hard, meaning that their worst-case complexity grows exponentially with the size of the problem. This means that as the number of state variables, actions and goals in the problem domain increases, the search space grows exponentially, making it very difficult to find a plan that satisfies the specified goal. This thesis is concerned with investigating these NP-hard domains, specifically by simplifying these domains into ones that have a polynomial solving time, creating a general policy of conditions and rules for which actions to take for the simplified domain, and then attempting to apply this policy onto the original domain. This creates a partial policy for the original domain, and the performance of this policy can be measured in order to judge its effectiveness. This can be explained as simplifying an intractable domain into a tractable one, creating a general policy for the tractable domain and then measuring its performance as a partial policy for the intractable domain. Classical Planning Planning Artificial Intelligence Transport Nurikabe NP-hard NP-hardness Computational Complexity Polynomial Polynomial Time P P-SPACE Planning Domain Planning Domains Planning Task Planning Tasks State States State Space General Policy Partial Policy Computer Systems Datorsystem

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Learning Partial Policies for Intractable Domains on Tractable Subsets. / Lärande av ofullständiga strategier för svårlärda domäner via lättlärda delmängder.