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You can modify the A* cost function to take the sensing cost into account: f(x) = g(x) + h(x) Just becomes: f(x) = (g(x) + [past sensing costs]) + (h
by 10000truths 5y ago
You can modify the A* cost function to take the sensing cost into account:
f(x) = g(x) + h(x)
Just becomes:
f(x) = (g(x) + [past sensing costs]) + (h(x) + [estimate of future sensing costs])
- thaumasiotes 5y agoWhy are you including [past sensing costs] in g(x)? The sensing costs aren't part of the cost of following the path; they're a cost of calculating it.
- 10000truths 5y agog(x) represents the costs that have been incurred thus far, since the starting point. How you wish to quantify and evaluate that cost is up to you as the implementer. For spatial navigation purposes, most people opt for “cost = Euclidean distance traversed”, but if Euclidean distance is not the only thing you’re trying to minimize, then your cost function must take other factors into account.
- thaumasiotes 5y agoBut look, the goal is "find the path that costs the least to traverse". The stated problem with A* is "running A* is too expensive". Why mix the outside-the-universe cost of running A* into the within-universe cost of traversing the path? If you've already paid the cost of scanning a path, the cost of using the knowledge you gained from that is still zero.