Riccardo Foffi

Sure, happy to start a PR, should be able to do it tomorrow (actually today, since midnight just clocked here). So, if I get what you are after, I'll change...

If the intention is to have useful general-use functions, random walks in `ContinuousSpace` allow for more freedom than just uniform random directions. It is rather easy to implement correlated random...

I'm rather busy now, but if noone else takes care of this before mid november I'll be happy to help. I guess it makes sense to first implement the `randomwalk!`...

I am starting to work on this. For the correlated random walks, `agent.vel` needs to be updated after each reorientation: 1 - is `agent.vel = new_direction` a safe / correct...

Shall we agree on a convention for euclidean spaces? If I had to choose, I would round the step to the on-grid distance which is closest to the given `r`....

The tests (at least most of them) fail because they pass tuples to `add_agent!`, construct agents using tuples, call other distance evaluation functions using tuples etc... Should I just put...

As a start I just focused on [continuous_space_tests.jl](https://github.com/JuliaDynamics/Agents.jl/blob/83129042f01673f832e4a32de53b93ecd6af80ab/test/continuous_space_tests.jl) Made some more updates to the functions that I originally missed and converted tuples to svectors in these tests. Some of the...

Just realised that `nearby_ids` works with the `GridSpace` that underlies the `ContinuousSpace`, so everything going through to `GridSpace` must be a tuple. It seems like a simple tuple conversion here...

I forgot to include a `using StaticArrays` in `runtests.jl`. This is what I got now from runtests. There is still something happening with pathfinding but I didn't look into it...

Sorry I have been away for a while due to conferences and holidays. I have some interest in moving forward with this pr. I can start by addressing the reviews...