LOLA breaks when changing number of actions and/or states

I try to edit IPD to a setup with four actions. This yields a 4x4 payoff matrix and a 17-dimensional input, which breaks both LOLA and LOLA-DiCE implementations.

- train_exact.py assumes that NUM_ACTIONS = 4 and NUM_STATES = 5 in the environment.
- Isn't the number of states also depending on number of actions: NUM_STATES = NUM_ACTIONS ** 2 + 1?
- As the payoff for agent 2 is simply the transposed payoff matrix: Does the game have to by symmetric? Or are different payoffs per agent possible in the current implementation?