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Toy problems were invented with the aim to program an AI which can solve it. The blocks world domain is an example for a toy problem. Its major advantage over more realistic AI applications is, that many algorithms and software programs are available which can handle the situation. [2] This allows to compare different theories against each other.
The agent must stack the blocks such that A is atop B, which in turn is atop C. However, it may only move one block at a time. The problem starts with B on the table, C atop A, and A on the table: However, noninterleaved planners typically separate the goal (stack A atop B atop C) into subgoals, such as: get A atop B; get B atop C
NP-complete special cases include the edge dominating set problem, i.e., the dominating set problem in line graphs. NP-complete variants include the connected dominating set problem and the maximum leaf spanning tree problem. [3]: ND2 Feedback vertex set [2] [3]: GT7 Feedback arc set [2] [3]: GT8 Graph coloring [2] [3]: GT4
Depth-first search (DFS) is an algorithm for traversing or searching tree or graph data structures. The algorithm starts at the root node (selecting some arbitrary node as the root node in the case of a graph) and explores as far as possible along each branch before backtracking.
SHRDLU is an early natural-language understanding computer program that was developed by Terry Winograd at MIT in 1968–1970. In the program, the user carries on a conversation with the computer, moving objects, naming collections and querying the state of a simplified "blocks world", essentially a virtual box filled with different blocks.
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To apply the event calculus, given the definitions of the , , , < and predicates, it is necessary to define the predicates that describe the specific context of the problem. For example, in the blocks world domain, we might want to describe an initial state in which there are two blocks, a red block on a green block on a table, like a toy ...
Formally, a parity check matrix H of a linear code C is a generator matrix of the dual code, C ⊥. This means that a codeword c is in C if and only if the matrix-vector product Hc ⊤ = 0 (some authors [1] would write this in an equivalent form, cH ⊤ = 0.) The rows of a parity check matrix are the coefficients of the parity check equations. [2]