Implements some static action selection algorithms [A, ACTION] = STATICACT(A, STATE, ACTIONS, REWARDS, PARAMS) Implements a set of static action selection algorithms. They are selected via the following learning parameters: 'static.type' - either one of the following: 'fixed' - a fixed number (the default) 'noisy' - a uniformly distributed random number with the mean around a given number 'rand' - random choice between discrete actions. Naturally, actions must be discrete 'sequence' - a predefined sequence of actions (e.g., derived from the optimal policy) 'static.value' - the fixed value for 'fixed', mean for 'noisy', the sequence of actions for 'sequence'. Default 0 'static.stdev' - noise standard deviation, for 'noisy'. Default 0.1. See also agent_act