The Physical Travelling Salesman Challenge

mikejuk writes "You probably know that the traveling salesman problem is one of the classics of computer science theory. Now we have a new challenge — the Physical Travelling Salesman Problem and anyone can join in. All you have to do is visit each city once using an optimal route. The new element is that you now have to drive between the cities using a 'car' that has inertia and friction — see the video. You can submit an AI bot to solve the problem or drive the course yourself."

Comments

sounds familiar

[fche]

Sounds like a relative of the ICFP 2008 contest: http://www.cs.uchicago.edu/newsletter/353

Uh, okay?

[TWX]

I thought the point of the actual mathematical problem was to mathematically conclude the best possible path, with the understanding that it wouldn't be real-world achievable but that one would use that as a guideline to strive for.

This little game they came up with removes the math portion of the experiment entirely, and while it adds the acceleration changes due to mass, one could have just introduced those acceleration changes into the original problem mathematically.

I don't understand what the little game is actually for. It's not entertaining enough despite their attempts to compare it to Crazy Taxi and others, and without there being math involved in plotting the route I don't see how one practices the theory beyond a child's level.

Re:Uh, okay?

[Corporate Drone]

It's simply meant to be an implementation of a heuristic, based on the traveling salesman problem, that takes into account physical considerations (speed, acceleration, direction) and processing limitations (RAM, processor cycles) for both initial setup and decision-making at each step.

The speed/direction stuff reminds me of the kind of skating that hockey players do (is it more effective to go in one direction, stop, and turn around, or is it better to modify your line and preserve momentum? in this game, too, is it better to accelerate greatly and bounce off a wall behind your target, or approach more slowly in order to modify your line without an abrupt change in direction?).

The processing limitations are interesting too, and provide for an interesting optimization exercise.

Or, by "I don't understand", should I simply answer "it's fun"...? ;)

Re:Uh, okay?

[gnasher719]

I thought the point of the actual mathematical problem was to mathematically conclude the best possible path, with the understanding that it wouldn't be real-world achievable but that one would use that as a guideline to strive for.

The point of the mathematical problem was being a mathematical problem. In real life, you would first not look at the distance, but at the cost (taking into account fuel, wear and tear, cost of the time spent, tolls etc. ). You would consider that the cost of going from A to B is often not the same as the cost going from B to A. You would consider that the cost will depend on the time of day. You will consider that there are other restrictions (be at X anytime before launch, be back at the base before 6pm). If a truck makes delivery, there might be advantages of getting rid of a heavy load early, so the cost would go down after visiting some point X.

So the result of the mathematical problem will likely not be nearly as good as some rather simple heuristic with real life data.

This is pointless...

[moosehooey]

The traveling salesman problem is based on a table of distances between the city pairs. It doesn't matter to the problem HOW those distances are calculated, or even if they include other variables. So this can be trivially reduced to the classic version of the problem.

Re:This is pointless...

[gnasher719]

The traveling salesman problem is based on a table of distances between the city pairs. It doesn't matter to the problem HOW those distances are calculated, or even if they include other variables. So this can be trivially reduced to the classic version of the problem.

It's not quite as simple. The distance between two destinations is not fixed. The time to get from A to B depends on the speed and direction when you arrived at A or passed through A, and the speed and direction that you want to have when arriving at B.

PTSP Motivation

[dperez]

Hi, I'm the organiser of the competition. The PTSP is meant to be a benchmark where different AI techniques can be tried and tested. This game gathers many of the features that real-time video games have (pathfinding, navigation, obstacle avoidance...). The objective is to provide a benchmark where new AI techniques can be tested and potentially exported to real time games. Of course the objective is not to solve the TSP. Actually, it's been seen that optimal TSP solutions, if we just consider the distances between the waypoints, do not create optimal PTSP paths. This makes the problem harder than just applying one of the very well known techniques to solve the TSP. Currently we have a couple of submissions that are behaving quite well, but there could be still room for improvement! Cheers, Diego.

Level Up

[arisvega]

What's next, the Relativistic Travelling Salesman problem? How about that for a challenge!