A Hamiltonian path in a graph is a path that visits all the nodes/vertices exactly once, a hamiltonian cycle is a cyclic path, i.e. all nodes visited once and the start and the endpoint are the same.
If we want to solve the snake game using this, we could divide the playable space in a grid and then try to just keep traversing on a hamiltonian cycle, this ...
Your approach seems reasonable to me. The edges do not necessarily have to be numbers, but, if you wish, you could also encode the actions as numbers. For example, the weight of an edge could represent the "cost" of the corresponding action. If there's no natural cost associated with an action, then you can add a unit cost for each action.
Welcome to AI.SE @GundamOfOasis!
Your intuition is right: this is fundamentally a problem for combinatorial search.
You're also right that problems are created by the fact that not every move is valid at state. To fix this, you need to add a function that can determine whether a given state is valid or not, in addition to the usual function that checks ...
Notice that a partition (set of nodes with the same label) can never get combined with another partition during an iteration. If two nodes are in different partitions, they stay in different partitions. If two nodes are in the same partition, they might stay in the same partition or get split up into different partitions. Therefore, the number of partitions ...
In spectral clustering we not find the eigenvectors of a graph (a graph is not a matrix) but the eigenvalues/eigenvectors of the Laplacian matrix related to the adjacency matrix of the graph:
graph => adjacency matrix => Laplacian matrix => eigenvalues (spectrum).
The adjacency matrix describes the "similarity" between two graph vertexs. ...
Each node is a position in the arrays
values = value of the node
conn = indexes of connected nodes
If its an undirected graph, each node must have all the nodes to which they are attached.
Instead, in directed graphs, only the start node has the index.
For your image:
values = ['A','B','C','D','E']
conn = [[1,2,3],[0,4],[0,3,4],[0,2,3],[1,3]]
Example = '...
I think there are different ways to solve the problem you presented:
1) It could be seen as classical resource optimization problem that can be solved via Linear Programming setup (highly suggested taking a look, not everything needs ML). You can find some resources here and quick intro to LP here
Linear Programming (LP) is a mathematical procedure for ...
Your question is still nearly perfectly unclear, but let's make a few guesses in order to make some progress.
The biggest mystery are your time slices:
How many of them you need? With more granular time, you get more unknowns and more constraints and the complexity grows quickly.
When someone gets a car, they probably use it to travel somewhere, so it may ...