Perception-NAR / Nalifier

gistfile1.txt

import sys

#identify instance as existing instance if matching better than this value, else create new one:
SUFFICIENT_MATCH_EXP = sys.argv[1] if len(sys.argv) > 1 else 0.5
TRUTH_EVIDENTAL_HORIZON = 1

def Truth_c2w(c):
    return TRUTH_EVIDENTAL_HORIZON * c / (1 - c);

def Truth_w2c(w):
    return w/(w + TRUTH_EVIDENTAL_HORIZON) if w > 0 else 0

def Truth_w2f(w_plus, w_minus):
    return w_plus / (w_plus + w_minus) if w_plus + w_minus > 0 else 0.5

def TruthValue(w_plus, w_minus):
    return (Truth_w2f(w_plus, w_minus), Truth_w2c(w_plus + w_minus))
    
def Truth_Abduction(v1, v2):
    ((f1,c1), (f2,c2)) = (v1, v2)
    return (f2, Truth_w2c(f1 * c1 * c2))

def Truth_Induction(v1, v2):
    return Truth_Abduction(v2, v1)

def Truth_Revision(v1, v2):
    MAX_CONFIDENCE = 0.99
    ((f1,c1), (f2,c2)) = (v1, v2)
    w1 = Truth_c2w(c1)
    w2 = Truth_c2w(c2)
    w = w1 + w2
    if w == 0.0:
        return (0.5, 0.0)
    return ( min(1.0, (w1 * f1 + w2 * f2) / w), min(MAX_CONFIDENCE, max(max(Truth_w2c(w), c1), c2)))

#Positive evidence collection:
#Case 1: A and B share a common property C
#A --> C
#B --> C
#derive:
#w+ for A --> B

#Case 2: A and B share a common instance
#A --> C
#B --> C
#derive:
#w+ for A --> B

#Case 3: B has a property which B does not have
#B --> C
#not A --> C
#derive:
#w- for A --> B

#Case 4: A has an instance which B does not have
#C --> A
#not C --> B
#derive:
#w- for A --> B

def inheritances(terms, isTuple=False):
    Inheritances = dict([])
    for i, term1 in enumerate(terms):
        (extension1, intension1) = terms[term1]
        for j, term2 in enumerate(terms):
            if i != j:
                (extension2, intension2) = terms[term2]
                w_plus = 0
                w_minus = 0
                truth2 = (0.5, 0.0)
                truth3 = (0.5, 0.0)
                for prop1, T1 in intension1:
                    for prop2, T2 in intension2:
                        if prop1 == prop2:
                            w_plus+=1
                            truthPlus = (1.0, 0.5)
                            truth2 = Truth_Revision(truth2, truthPlus)
                            truth3 = Truth_Revision(truth3, Truth_Induction(T1, T2))
                for prop1, T1 in extension1:
                    for prop2, T2 in extension2:
                        if prop1 == prop2:
                            w_plus+=1
                            truthPlus = (1.0, 0.5)
                            truth2 = Truth_Revision(truth2, truthPlus)
                            truth3 = Truth_Revision(truth3, Truth_Abduction(T1, T2))
                for prop2, T2 in intension2:
                    AHasProperty = False
                    for prop1, T1 in intension1:
                        if prop1 == prop2:
                            AHasProperty = True
                    if not AHasProperty:
                        w_minus+=1
                        truthMinus = (0.0, 0.5)
                        truth2 = Truth_Revision(truth2, truthMinus)
                        T1 = (0.0, 1.0) #fabricated truth since the property does not appear in T1
                        truth3 = Truth_Revision(truth3, Truth_Induction(T1, T2))
                for inst1, T1 in extension1:
                    BHasInstance = False
                    for inst2, T2 in extension2:
                        if inst1 == inst2:
                            BHasInstance = True
                    if not BHasInstance:
                        w_minus+=1
                        truthMinus = (0.0, 0.5)
                        truth2 = Truth_Revision(truth2, truthMinus)
                        T2 = (0.0, 1.0) #fabricated truth since the property does not appear in T1
                        truth3 = Truth_Revision(truth3, Truth_Abduction(T1, T2))
                statement = "<{" + term2 + "} --> [see]>. :|:"
                Inheritances[statement] = truth3
                #see: all ways to calculate the truth are equal, unless terms contains c < 1 entries which is only captured by the NAL way, truth3:
                #print(statement, w_plus, w_minus, TruthValue(w_plus, w_minus), truth2, truth3)
        if isTuple: break
    return Inheritances

def Truth_Expectation(T):
    (f,c) = T
    return (c * (f - 0.5) + 0.5)
    
prototypes = {}
current_prototypes = {}
last_instance = None
last_winner = None
last_winner_truth_exp = 0.0

def NAL_AddInput(inp): #<{instance} --> [property]>. :|: %frequency%
    global current_prototypes, prototypes, last_instance, last_winner, last_winner_truth_exp
    if inp != "1":
        instance = inp.split("{")[1].split("}")[0]
        property = inp.split("[")[1].split("]")[0]
        frequency = float(inp.split("%")[1].split("%")[0].split(";")[0]) if "%" in inp else 1.0
    if inp == "1" or (instance != last_instance and last_instance is not None):
        #DETERMINE BEST MATCH IN CURRENT PROTOTYPES:
        if last_winner is not None and last_winner_truth_exp > SUFFICIENT_MATCH_EXP:
            for k,v in last_winner.items(): #just 1
                print(f"{k} %{v[0]};{v[1]}%" )
        else:
            print("<{" + last_instance + "} --> [see]>. :|:")
            prototypes.update(current_prototypes)
        current_prototypes = {}
    if inp == "1":
        return
    last_instance = instance
    print("//" + inp)
    if instance not in current_prototypes:
        current_prototypes[instance] = (set(),set())
    current_prototypes[instance][1].add((property, (frequency, 0.9)))
    winner = None
    winner_truth_exp = 0.0
    for (key, value) in prototypes.items():
        terms = {instance: current_prototypes[instance], key: value}
        candidate = inheritances(terms, True)
        candidate_truth_exp = Truth_Expectation(list(candidate.values())[0])
        if candidate_truth_exp > winner_truth_exp:
            winner = candidate
            winner_truth_exp = candidate_truth_exp
    last_winner_truth_exp = winner_truth_exp
    last_winner = winner

print("*volume=0")
NAL_AddInput("<{scoobydoo} --> [furry]>. :|:")
NAL_AddInput("<{scoobydoo} --> [brown]>. :|:")
NAL_AddInput("<{scoobydoo} --> [barks]>. :|:")
NAL_AddInput("<{scoobydoo} --> [loud]>. :|:")
NAL_AddInput("<{garfield} --> [furry]>. :|:")
NAL_AddInput("<{garfield} --> [yellow]>. :|:")
NAL_AddInput("<{garfield} --> [meows]>. :|:")
NAL_AddInput("<{garfield} --> [loud]>. :|: %0.0%")
NAL_AddInput("<{duck} --> [feathered]>. :|:")
NAL_AddInput("<{duck} --> [yellow]>. :|:")
NAL_AddInput("<{duck} --> [quacks]>. :|:")
NAL_AddInput("<{duck} --> [loud]>. :|:")
NAL_AddInput("<{anon} --> [feathered]>. :|: %0.6%")
NAL_AddInput("<{anon} --> [barks]>. :|:")
NAL_AddInput("<{anon} --> [loud]>. :|:")
NAL_AddInput("<{anon} --> [yellow]>. :|:")
NAL_AddInput("1")