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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.
17 indivisible camels. The 17-animal inheritance puzzle is a mathematical puzzle involving unequal but fair allocation of indivisible goods, usually stated in terms of inheritance of a number of large animals (17 camels, 17 horses, 17 elephants, etc.) which must be divided in some stated proportion among a number of beneficiaries.
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.
By restricting ourselves to reversible actions only, we can construct the solution to the problem from the desired result. From the point [4,4,0], there are only two reversible actions: transferring 3 liters from the 8 liter jug to the empty 3 liter jug [1,4,3], and transferring 3 liters from the 5 liter jug to the empty 3 liter jug [4,1,3].
Identifying new macro operators for a domain can be realized with genetic programming. [4] The idea is, not to plan the domain itself, but in the pre-step, a heuristics is created that allows the domain to be solved much faster. In the context of reinforcement learning, a macro-operator is called an option. Similar to the definition within AI ...
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The Giants have yielded the fifth-most schedule-adjusted fantasy points to running backs over the last five weeks, so Williams is a DFS building block. Rashee Rice ($26) vs. Cincinnati Bengals