#prompt | #protocol #code #smart-autonomous-agent #scenario
Expanding on [[2024-11-30#^80da20]]
Imagine I have a bunch of agents that I feed with a protocol whose good enough outcome is to take an open room filled with stuff from distribution A to distribution B. The condition of being open is important here as it allows the solvant state B to never be achieved once and for all but at least you can get close to it, because other coexisting agents and hyperobjects keep injecting entropy into the process undertaken by your SSAs as a network.
Now for me to have a protocol over these SSAs in order to perform the task, I need an '*Action Abstraction*' so that I can have modes of action to use without caring about their details, then use these modes of action in writing the rules. Back to my example, I should be able to speak about modes like, Idle, Accessing (evaluating local conditions against desired distribution), and Rebalancing (acting to shift local conditions closer to the target) without caring about their detail and assume that it is defined.
```protocol
protocol DistributionProtocol {
// Define local modes
mode Idle {
on_timer(tick) -> Transition to Assessing;
}
mode Assessing {
on_condition(deviation_from_target > tolerance) -> {
emit Signal(StateDeviation);
Transition to Rebalancing;
}
on_condition(deviation_from_target <= tolerance) -> Transition to Idle;
}
mode Rebalancing {
on_entry {
perform Action(AdjustLocalConditions, adjustment_parameters);
}
on_action_complete(AdjustLocalConditions) -> {
emit Signal(ActionTaken);
Transition to Assessing;
}
}
// Define signal handlers
on_signal(StateDeviation) {
if state == Idle {
emit Signal(AcknowledgedDeviation);
}
}
on_signal(ActionTaken) {
if state == Assessing {
adjust_rebalancing_strategy();
}
}
// Utility Functions
function deviation_from_target {
return calculate_difference(local_state, target_state);
}
function adjust_rebalancing_strategy {
modify_parameters(adjustment_parameters, signal.data);
}
}
```