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A partially observable Markov decision process ( POMDP) is a generalization of a Markov decision process (MDP). A POMDP models an agent decision process in which it is assumed that the system dynamics are determined by an MDP, but the agent cannot directly observe the underlying state. Instead, it must maintain a sensor model (the probability ...
PY, PYW – Python code file; PMP – PenguinMod Project; PMS – PenguinMod Sprite; RAR – RAR Rar Archive, for multiple file archive (rar to .r01-.r99 to s01 and so on) RAG, RAGS – Game file, a game playable in the RAGS game-engine, a free program which both allows people to create games, and play games, games created have the format "RAG ...
O(n)[ 1] In computer science, a disjoint-set data structure, also called a union–find data structure or merge–find set, is a data structure that stores a collection of disjoint (non-overlapping) sets. Equivalently, it stores a partition of a set into disjoint subsets. It provides operations for adding new sets, merging sets (replacing them ...
The intermediate (thin) rectangles represent the hypotheses in the version space. Version space learningis a logicalapproach to machine learning, specifically binary classification. Version space learning algorithms search a predefined space of hypotheses, viewed as a set of logical sentences. Formally, the hypothesis space is a disjunction[1]
In computational learning theory, probably approximately correct ( PAC) learning is a framework for mathematical analysis of machine learning. It was proposed in 1984 by Leslie Valiant. [ 1] In this framework, the learner receives samples and must select a generalization function (called the hypothesis) from a certain class of possible functions.
A JVM language is any language with functionality that can be expressed in terms of a valid class file which can be hosted by the Java Virtual Machine. A class file contains Java Virtual Machine instructions (Java byte code) and a symbol table, as well as other ancillary information. The class file format is the hardware- and operating system ...
Constraint satisfaction problem. Constraint satisfaction problems ( CSPs) are mathematical questions defined as a set of objects whose state must satisfy a number of constraints or limitations. CSPs represent the entities in a problem as a homogeneous collection of finite constraints over variables, which is solved by constraint satisfaction ...
Apriori[ 1] is an algorithm for frequent item set mining and association rule learning over relational databases. It proceeds by identifying the frequent individual items in the database and extending them to larger and larger item sets as long as those item sets appear sufficiently often in the database. The frequent item sets determined by ...