# Algorithm: Collaborative Message Response and Harmonization
# --------------------------------------------------------------------------
# Part 1: Main Algorithm (msg1 to msg2 Flow)
# --------------------------------------------------------------------------
# Assumptions:
# - Agents L and R exist.
# - fpmsg primitives (perceive, output, empathize, diplomat) are available.
# - Input message 'msg1' is received. # implicitly "text out: msg1"
# Initial Perception of msg1
fp_msg1_L = perceive(msg1)
fp_msg1_R = perceive(msg1)
# Inscription of Initial Perception
msg1_L = output(fp_msg1_L) # text out: msg1-L
msg1_R = output(fp_msg1_R) # text out: msg1-R
# Initiate Shared Construction
# Establish agreement on the initial shared state representation.
fp_initial_shared = Define_Initial_Shared_FP() # Function returning the agreed initial fingerprint
Initialize msg_shared_artifact # Create the initial shared artifact (e.g., blank or based on msg1)
# Personal mementos reflect the agreed initial state
msg_shared_L_init = output(fp_initial_shared) # text out: msg-shared-L (initial)
msg_shared_R_init = output(fp_initial_shared) # text out: msg-shared-R (initial)
# Execute Harmonization Loop to build/refine msg_shared_artifact
# Pass the initial shared artifact and the single agreed initial fingerprint.
# The loop will internally update 'msg_shared_artifact', and generate updated 'msg_shared_L', 'msg_shared_R'.
status, resulting_message = Harmonization_Loop(msg_shared_artifact, fp_initial_shared) # resulting_message is the final "text out: msg-shared"
# Determine Final Outcome based on Harmonization Loop result
IF (status == 'AgreementReached') THEN
msg2 = resulting_message # Successful collaboration
Display/Send(msg2) # text out: msg2
ELSE # status == 'FocusLost'
new_msg1 = resulting_message # Incomplete harmonization result becomes input for next attempt
Handle_Harmonization_Failure(new_msg1) # E.g., restart process with new_msg1 or signal error
ENDIF
# --------------------------------------------------------------------------
# Part 2: Harmonization Loop Function
# --------------------------------------------------------------------------
# Defines the iterative process for refining the shared message artifact.
# Function accepts the initial msg artifact and the single initial agreed FP.
FUNCTION Harmonization_Loop(initial_msg_artifact, initial_fp_shared):
# Initialize working variables for the loop from the inputs.
current_msg_artifact = initial_msg_artifact # Represents the evolving "text out: msg-shared"
current_fp_L = initial_fp_shared
current_fp_R = initial_fp_shared
# Loop continues while both agents are focused and agreement isn't reached.
WHILE (Agent L is focused AND Agent R is focused AND NOT Agents_Agree(current_msg_artifact, current_fp_L, current_fp_R))
# Store Previous States (Concurrent)
fp_previous_L = current_fp_L
fp_previous_R = current_fp_R
# Perception Phase (Concurrent)
fp_msg_shared = perceive(current_msg_artifact) # Perceive the current "text out: msg-shared"
# --- Adjustment Phase (Concurrent) ---
# -- Agent L's Adjustment --
inhale_signal_L = empathize(target_fp=fp_msg_shared, current_fp=fp_previous_L)
exhale_signal_L = empathize(target_fp=fp_previous_L, current_fp=fp_msg_shared)
self_resonance_signal_L = empathize(target_fp=fp_previous_L, current_fp=fp_previous_L)
current_fp_L = diplomat(fp_previous_L, inhale_signal_L) # Note: diplomat implementation defines adjustment logic
msg_shared_L = output(current_fp_L) # text out: msg-shared-L (L's updated private memento)
# -- Agent R's Adjustment --
inhale_signal_R = empathize(target_fp=fp_msg_shared, current_fp=fp_previous_R)
exhale_signal_R = empathize(target_fp=fp_previous_R, current_fp=fp_msg_shared)
self_resonance_signal_R = empathize(target_fp=fp_previous_R, current_fp=fp_previous_R)
current_fp_R = diplomat(fp_previous_R, inhale_signal_R) # Note: diplomat implementation defines adjustment logic
msg_shared_R = output(current_fp_R) # text out: msg-shared-R (R's updated private memento)
# --- Contribution Phase ---
# Agents contribute modifications to the shared artifact based on their updated states.
current_msg_artifact = Update_Shared_Message(current_msg_artifact, current_fp_L, current_fp_R, exhale_signal_L, exhale_signal_R)
# Note: Update_Shared_Message implementation defines contribution logic.
END WHILE
# Determine loop termination reason and return status/result.
IF (Agents_Agree(current_msg_artifact, current_fp_L, current_fp_R)) THEN
RETURN 'AgreementReached', current_msg_artifact # Return the final "text out: msg-shared"
ELSE # Loop terminated due to focus loss
RETURN 'FocusLost', current_msg_artifact # Return the final "text out: msg-shared"
ENDIF
END FUNCTION
# Helper functions assumed to exist:
# - Define_Initial_Shared_FP(): Returns the fingerprint agreed upon by L and R to start harmonization.
# - Agents_Agree(msg_artifact, fpL, fpR): Returns TRUE if agents agree msg_artifact is complete. (Implementation details vary)
# - Update_Shared_Message(msg_artifact, fpL, fpR, exhL, exhR): Returns modified msg_artifact based on agent states/contributions. (Implementation details vary)
# - Handle_Harmonization_Failure(msg_artifact): Procedure for handling failed harmonization.
Summary of "text out" Message Artifacts
msg1: Initial input message. (Implicit input)
msg1-L: Agent L's inscribed perception of msg1. (msg1_L)
msg1-R: Agent R's inscribed perception of msg1. (msg1_R)
msg-shared-L (initial): Agent L's initial memento of shared state agreement. (msg_shared_L_init)
msg-shared-R (initial): Agent R's initial memento of shared state agreement. (msg_shared_R_init)
msg-shared: The evolving shared artifact. (msg_shared_artifact, current_msg_artifact, resulting_message)
msg-shared-L (updated): Agent L's updated private memento within the loop. (msg_shared_L)
msg-shared-R (updated): Agent R's updated private memento within the loop. (msg_shared_R)
msg2: Final message if successful harmonization. (msg2)
(new) msg1: Final artifact state if harmonization fails. (new_msg1)
Concluding Note on Implementation and Research:
This algorithm provides a conceptual framework for collaborative response using fpmsg primitives and a shared artifact. The specific logic within functions like diplomat or Update_Shared_Message are illustrative suggestions, as optimal implementations depend heavily on the application context. Understanding and refining communication dynamics mediated by shared artifacts and fingerprint representations remains an active area of research.
here's fpmsg for context
fp msg
perceive(msg) extracts msg-fp from msg
empathize(target_fp, current_fp) derives how to change current_fp towards target_fp, outputs the result as a fingerprint (fp) ready for the diplomat function
diplomat(fp1, fp2, fp3,...) combines fingerprints (fp), outputs a fingerprint (fp)
output(fp) generates a msg from fp
delay({fp,msg}, t) returns fingerprint or message delayed by time t
eg output(diplomat(perceive(msg), empathize(fp1, fp2)))
eg output(diplomat(diplomat(perceive(msg3), perceive(msg2)*0.3), perceive(msg1)*0.1))
eg output(diplomat(empathize(perceive(msgA1), perceive(msgB1)), perceive(msgA2)))
eg output(diplomat(perceive(msg1), perceive(msg2) * -1.0))
eg output(delay(perceive(msg), 10))
eg output(diplomat(fp1, fp2 * msg))
eg output(diplomat(perceive(msg1), perceive(msg2) * output(diplomat(perceive(msgx), perceive(delay(msgx, t)) * -1.0))))
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