Revert individual entropy

Also do some fixes to the python code:

- Changed tmin to 8
- Changed delta to 2, which is the right value according to the original
- fix for overcounting ticks when timing out
Ensure dogs start in the same position every time
Make sure tick amount get set to max if cat wins

That's the key to proper interest values!
The "max ticks if won" was a red herring, fixed.

The real problem was that the PFB-cat had its costs all wrong and never
behaved properly.

I have now gone by the assumption that cost function of the original
thesis had a very different scale than mine, so the hill cost was
scaled correctly. I set it to a hundreth (10), as this seems to give
good behaviour versus the follower dog ai.

In doing so I also removed the "scaling factor" I had applied to  the
exit cost which is now irrelevant. Hopefully this will finally lay to
rest the problems we are having in the simulation.
Added support for trials

- Datalogger now supports trials
- PFB-cat can now have a variable dog cost
- Current trial setup is for checking the optimal dog cost