In this case the neighborhood is defined relative to some subset of binary variables reachable by some operation that depends on the problem. This is what is generally meant by a neighborhood in heuristic search in general, and tabu search in particular, where a move is defined in terms of neighbors. Nelder-Mead simplex method . This is divided into the following cases. A collection of nodes , V, sometimes called vertices , plus a collection of arcs , A, which are directed from one node to another.
Network flows .
A network where the nodes correspond to neurons and the arcs correspond to synaptic connections in the biological metaphor. Each node has a state variable, say x. Each arc has a weight that affects the state of its neighboring nodes when firing. Various learning mechanisms are represented this way, including a form of supervised learning that uses a training set to provide feedback on errors. Other elements can be learned besides the arc weights, including the topology of the network.