Merge pull request singnet#40 from ngeiswei/merge-opencog-to-singnet

Merge opencog -> singnet
TScottJ · Oct 14, 2021 · a737b49 · a737b49
2 parents a804991 + 7933f0e
commit a737b49
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Showing 3 changed files with 57 additions and 45 deletions.
diff --git a/examples/cartpole.py b/examples/cartpole.py
@@ -120,7 +120,7 @@ def plan(self, goal, expiry) -> List:
 
         The format for a cognitive schematic is as follows
 
-        PredictiveImplicationScope <tv>
+        BackPredictiveImplicationScope <tv>
           <vardecl>
           <expiry>
           And (or SimultaneousAnd?)
@@ -152,7 +152,7 @@ def plan(self, goal, expiry) -> List:
         hTV = TruthValue(0.9, 0.1)  # High TV
         lTV = TruthValue(0.1, 0.1)  # Low TV
 
-        # PredictiveImplicationScope <high TV>
+        # BackPredictiveImplicationScope <high TV>
         #   TypedVariable
         #     Variable "$angle"
         #     Type "NumberNode"
@@ -169,7 +169,7 @@ def plan(self, goal, expiry) -> List:
         #   Evaluation
         #     Predicate "Reward"
         #     Number "1"
-        cs_rr = PredictiveImplicationScopeLink(
+        cs_rr = BackPredictiveImplicationScopeLink(
             TypedVariableLink(angle, numt),
             time_offset,
             AndLink(
@@ -185,7 +185,7 @@ def plan(self, goal, expiry) -> List:
             tv=hTV,
         )
 
-        # PredictiveImplicationScope <high TV>
+        # BackPredictiveImplicationScope <high TV>
         #   TypedVariable
         #     Variable "$angle"
         #     Type "NumberNode"
@@ -202,7 +202,7 @@ def plan(self, goal, expiry) -> List:
         #   Evaluation
         #     Predicate "Reward"
         #     Number "1"
-        cs_ll = PredictiveImplicationScopeLink(
+        cs_ll = BackPredictiveImplicationScopeLink(
             TypedVariableLink(angle, numt),
             time_offset,
             AndLink(
@@ -222,7 +222,7 @@ def plan(self, goal, expiry) -> List:
         # actions, i.e. going left when the pole is falling to the right
         # and such, which should make the situation worse.
 
-        # PredictiveImplicationScope <low TV>
+        # BackPredictiveImplicationScope <low TV>
         #   TypedVariable
         #     Variable "$angle"
         #     Type "NumberNode"
@@ -239,7 +239,7 @@ def plan(self, goal, expiry) -> List:
         #   Evaluation
         #     Predicate "Reward"
         #     Number "1"
-        cs_rl = PredictiveImplicationScopeLink(
+        cs_rl = BackPredictiveImplicationScopeLink(
             TypedVariableLink(angle, numt),
             time_offset,
             AndLink(
@@ -255,7 +255,7 @@ def plan(self, goal, expiry) -> List:
             tv=lTV,
         )
 
-        # PredictiveImplicationScope <low TV>
+        # BackPredictiveImplicationScope <low TV>
         #   TypedVariable
         #     Variable "$angle"
         #     Type "NumberNode"
@@ -272,7 +272,7 @@ def plan(self, goal, expiry) -> List:
         #   Evaluation
         #     Predicate "Reward"
         #     Number "1"
-        cs_lr = PredictiveImplicationScopeLink(
+        cs_lr = BackPredictiveImplicationScopeLink(
             TypedVariableLink(angle, numt),
             time_offset,
             AndLink(

diff --git a/rocca/agents/core.py b/rocca/agents/core.py
@@ -91,13 +91,9 @@ def load_opencog_modules(self):
         # Load PLN.  All rules must be pre-loaded here
         scheme_eval(self.atomspace, "(use-modules (opencog pln))")
         scheme_eval(self.atomspace, "(use-modules (opencog spacetime))")
-        scheme_eval(
-            self.atomspace,
-            "(pln-load-rule 'predictive-implication-scope-direct-evaluation)",
-        )
-        scheme_eval(
-            self.atomspace, "(pln-load-rule 'predictive-implication-scope-deduction)"
-        )
+        rules = ["back-predictive-implication-scope-direct-evaluation",
+                 "back-predictive-implication-scope-deduction-cogscm"]
+        self.pln_load_rules(rules)
         # scheme_eval(self.atomspace, "(pln-log-atomspace)")
 
     def reset_action_counter(self):
@@ -138,6 +134,20 @@ def make_goal(self):
 
         return EvaluationLink(PredicateNode("Reward"), NumberNode(str(1)))
 
+    def pln_load_rules(self, rules=[]):
+        """Load PLN rules.
+
+        Take a list of rule scheme symbols (but without the single
+        quote for the symbol), such as
+
+        ["back-predictive-implication-scope-direct-evaluation",
+         "back-predictive-implication-scope-deduction-cogscm"]
+
+        """
+
+        for rule in rules:
+            scheme_eval(self.atomspace, "(pln-load-rule '" + rule + ")")
+
     def pln_bc(self, query, vardecl=None, maxiter=10, rules=[]):
         """Call PLN backward chainer with the given query and parameters.
 
@@ -152,11 +162,13 @@ def pln_bc(self, query, vardecl=None, maxiter=10, rules=[]):
 
         agent_log.fine("pln_bc(query={}, maxiter={})".format(query, maxiter))
 
-        # Load rules
+        # Add rules (should be previously loaded)
         if rules:
             scheme_eval(self.atomspace, "(pln-rm-all-rules)")
             for rule in rules:
-                scheme_eval(self.atomspace, "(pln-add-rule '" + rule + ")")
+                er = scheme_eval(self.atomspace, "(pln-add-rule '" + rule + ")")
+                agent_log.info("(pln-add-rule '" + rule + ")")
+                agent_log.info("er = " + str(er))
 
         # Generate and run query
         command = "(pln-bc "
@@ -247,9 +259,9 @@ def infer_cogscms(self):
         T = VariableNode("$T")
         P = VariableNode("$P")
         Q = VariableNode("$Q")
-        query = PredictiveImplicationScopeLink(V, T, P, Q)
+        query = BackPredictiveImplicationScopeLink(V, T, P, Q)
         mi = 10
-        rules = ["predictive-implication-scope-deduction"]
+        rules = ["back-predictive-implication-scope-deduction-cogscm"]
         cogscms = self.pln_bc(query, maxiter=mi, rules=rules)
 
         agent_log.fine("Inferred cognitive schematics = {}".format(cogscms))
@@ -369,7 +381,7 @@ def to_sequential_and(self, timed_clauses):
             early_events = get_events(early_clauses)
             latest_clauses = get_latest_clauses(timed_clauses)
             latest_events = get_events(latest_clauses)
-            return AltSequentialAndLink(
+            return BackSequentialAndLink(
                 to_nat(1), maybe_and(early_events), maybe_and(latest_events)
             )
         else:
@@ -417,7 +429,7 @@ def to_predictive_implication_scope(self, pattern):
 
         then the resulting predictive implication scope is
 
-        PredictiveImplicationScope
+        BackPredictiveImplicationScope
           VariableList
           S Z
           Execution
@@ -453,7 +465,7 @@ def to_predictive_implication_scope(self, pattern):
 
         then the resulting predictive implication scope is
 
-        PredictiveImplicationScope
+        BackPredictiveImplicationScope
           Variable "$X"
           S Z
           And
@@ -474,7 +486,7 @@ def to_predictive_implication_scope(self, pattern):
 
         then the resulting predictive implication (scope) is
 
-        PredictiveImplication <1 - s, c>
+        BackPredictiveImplication <1 - s, c>
           <antecedent>
           Evaluation
             Predicate "Reward"
@@ -503,11 +515,11 @@ def to_predictive_implication_scope(self, pattern):
         lag = SLink(ZLink())
 
         ntvardecl = self.get_nt_vardecl(pattern)
-        # TODO: fix python PredictiveImplicationScopeLink binding!
-        # preimp = PredictiveImplicationScopeLink(ntvardecl, lag, pt, pd)
+        # TODO: fix python BackPredictiveImplicationScopeLink binding!
+        # preimp = BackPredictiveImplicationScopeLink(ntvardecl, lag, pt, pd)
         preimp = scheme_eval_h(
             self.atomspace,
-            "(PredictiveImplicationScopeLink "
+            "(BackPredictiveImplicationScopeLink "
             + str(ntvardecl)
             + str(lag)
             + str(pt)
@@ -525,7 +537,7 @@ def to_predictive_implication_scope(self, pattern):
         agent_log.fine("preimp = {}".format(preimp))
         # Calculate the truth value of the predictive implication
         mi = 2
-        rules = ["predictive-implication-scope-direct-evaluation"]
+        rules = ["back-predictive-implication-scope-direct-evaluation"]
         return self.pln_bc(preimp, maxiter=mi, rules=rules)[0]
 
     def is_desirable(self, cogscm):
@@ -724,7 +736,7 @@ def plan(self, goal, expiry):
         information.  The supported format for cognitive schematics
         are as follows
 
-        PredictiveImplicationScope <tv>
+        BackPredictiveImplicationScope <tv>
           <vardecl>
           <lag-n>
           SequentialAnd [optional]

diff --git a/rocca/agents/utils.py b/rocca/agents/utils.py
@@ -259,7 +259,7 @@ def get_vardecl(cogscm):
 
     Given a cognitive schematic of that format
 
-    PredictiveImplicationScope <tv>
+    BackPredictiveImplicationScope <tv>
       <vardecl>
       <expiry>
       And (or SimultaneousAnd?)
@@ -272,7 +272,7 @@ def get_vardecl(cogscm):
 
     return <vardecl>.
 
-    If the cognitive schematic is an PredictiveImplicationLink then
+    If the cognitive schematic is an BackPredictiveImplicationLink then
     return an empty VariableSet.
 
     """
@@ -301,7 +301,7 @@ def get_context(cogscm):
 
     For instance given a cognitive schematic of that format
 
-    PredictiveImplicationScope <tv>
+    BackPredictiveImplicationScope <tv>
       <vardecl>
       <expiry>
       And
@@ -313,7 +313,7 @@ def get_context(cogscm):
 
     Another example, given a cognitive schematic of that format
 
-    PredictiveImplicationScope <tv>
+    BackPredictiveImplicationScope <tv>
       <vardecl>
       <expiry>
       SequentialAnd
@@ -359,13 +359,13 @@ def is_scope(atom):
 def is_predictive_implication(atom):
     """Return True iff the atom is a predictive implication link."""
 
-    return is_a(atom.type, get_type("PredictiveImplicationLink"))
+    return is_a(atom.type, get_type("BackPredictiveImplicationLink"))
 
 
 def is_predictive_implication_scope(atom):
     """Return True iff the atom is a predictive implication scope link."""
 
-    return is_a(atom.type, get_type("PredictiveImplicationScopeLink"))
+    return is_a(atom.type, get_type("BackPredictiveImplicationScopeLink"))
 
 
 def is_and(atom):
@@ -377,11 +377,11 @@ def is_and(atom):
 def is_sequential_and(atom):
     """Return True iff atom is a sequential and.
 
-    Also for now we use AltSequentialAndLink.
+    Also for now we use BackSequentialAndLink.
 
     """
 
-    return is_a(atom.type, get_type("AltSequentialAndLink"))
+    return is_a(atom.type, get_type("BackSequentialAndLink"))
 
 
 def is_execution(atom):
@@ -413,7 +413,7 @@ def get_antecedent(atom):
 
     For instance is the cognitive schematics is represented by
 
-    PredictiveImplicationScope <tv>
+    BackPredictiveImplicationScope <tv>
       <vardecl>
       <expiry>
       <antecedent>
@@ -437,7 +437,7 @@ def get_succedent(atom):
 
     For instance is the cognitive schematics is represented by
 
-    PredictiveImplicationScope <tv>
+    BackPredictiveImplicationScope <tv>
       <vardecl>
       <expiry>
       <antecedent>
@@ -459,9 +459,9 @@ def get_succedent(atom):
 def get_lag(atom):
     """Given an temporal atom, return its lag component.
 
-    For instance if it is a PredictiveImplicationScope
+    For instance if it is a BackPredictiveImplicationScope
 
-    PredictiveImplicationScope
+    BackPredictiveImplicationScope
       <vardecl>
       <lag>
       <antecedent>
@@ -494,7 +494,7 @@ def get_t0_clauses(antecedent):
 
     For instance if the cognitive schematics has the following format
 
-    PredictiveImplicationScope <tv>
+    BackPredictiveImplicationScope <tv>
       <vardecl>
       <lag>
       SequentialAnd
@@ -599,7 +599,7 @@ def get_total_lag(atom):
 
     For instance if the atom is
 
-    PredictiveImplicationScope <tv>
+    BackPredictiveImplicationScope <tv>
       <vardecl>
       <lag-1>
       SequentialAnd
@@ -628,7 +628,7 @@ def get_t0_execution(cogscm):
 
     Given a cognitive schematic of that formats
 
-    PredictiveImplicationScope <tv>
+    BackPredictiveImplicationScope <tv>
       <vardecl>
       <expiry>
       And (or SimultaneousAnd?)
@@ -657,7 +657,7 @@ def get_context_actual_truth(atomspace, cogscm, i):
 
     Given a cognitive schematic of that format
 
-    PredictiveImplicationScope <tv>
+    BackPredictiveImplicationScope <tv>
       <vardecl>
       <expiry>
       And (or SimultaneousAnd?)