Refactor configs

[laermannjan]

configs should now be dictionaries within the overarching Configs dictionary, like so:

Configs = {
    'config_name1': {
        'env': 'Acrobot-v1',
        'gamma': 0.99
        ...
    },
    'config_name2: {
        'env': 'LunarLander-v2',
        'gamma': 0.01
        ...
    },
    ....
}

Important: a 'basic' config should be defined for each environment, which sets the baseline parameters for all future adaptions in experiments. Per convention the names of those configs for LunarLander-v1, Acrobot-v2 and Cartpole-v0 are LL_basic, AB_basic and CP_basic, respectively. A specific config for an experiment, e.g. LL_exp1 must always contain the key env defining the environment of the experiment. Everything else is optional and can therefore be limited to only those keys which shall differ from the environment's baseline config (XX_basic).

Attention

key names used by the new training facility (ccbb561) have changed compared to the old configs. Some keys also have been dropped and others added. Check testbench.py for a full list of all keys and possible values. Note that an option name like --foo-bar translates into a key name foo_bar.

[laermannjan]

I refactored the new configs and integrated our test configs for LunarLander. We still need the AB_basic (this is currently just a copy of LL_basic to prevent crashes) and the respective test configs.

[bordeauxred]

Added Acrobot configs in 0aca8077907025ca1ddec6cc074f3420a86a882e

But we need to reevaluate AB_basic