Correct formula for Issue #57

pynars/Config.py

@@ -17,7 +17,7 @@ class Enable:
     debug = False
 
 class Config:
-    r_top_level_attention = 0.5
+    r_top_level_attention_adjust = 0.5
 
     priority: float=0.8
     durability: float=0.8

pynars/NARS/Control/Reasoner.py

@@ -42,6 +42,8 @@ def __init__(self, n_memory, capacity, config = './config.json', nal_rules={1,2,
         self.sequence_buffer = Buffer(capacity)
         self.operations_buffer = Buffer(capacity)
 
+        self.u_top_level_attention = 0.5
+
     def reset(self):
         ''''''
         # TODO
@@ -71,10 +73,16 @@ def cycle(self):
 
         random_number: float = random.random()
 
-        if random_number < Config.Config.r_top_level_attention:
+        data_structure_accessed_busyness = None
+        if random_number < self.u_top_level_attention:
             judgement_revised, goal_revised, answers_question, answers_quest = self.observe(tasks_derived)
+            data_structure_accessed_busyness = self.overall_experience.busyness
         else:
             self.consider(tasks_derived)
+            data_structure_accessed_busyness = self.memory.busyness
+
+        self.u_top_level_attention = Config.Config.r_top_level_attention_adjust * data_structure_accessed_busyness \
+                                     + (1 - Config.Config.r_top_level_attention_adjust) * self.u_top_level_attention
 
         #   temporal induction in NAL-7
         if Enable.temporal_reasoning and task is not None and task.is_judgement and task.is_external_event:

pynars/NARS/DataStructures/_py/Bag.py

@@ -58,6 +58,7 @@ def map_priority(priority: float):
             return idx if idx < self.n_levels else self.n_levels - 1
 
         self.map_priority = map_priority
+        self.busyness = 0.5
 
     def take(self, remove = True) -> Item:
         if len(self) == 0: return None

pynars/NARS/DataStructures/_py/Buffer.py

@@ -22,10 +22,12 @@ class Buffer(Bag):
         existing concepts in the memory or tasks in the buffer.
     '''
 
+
     def __init__(self, capacity: int, n_buckets: int=None, take_in_order: bool=False, max_duration: int=None) -> None:
         key: Callable[[Task], Any] = lambda task: (hash(task), hash(task.stamp.evidential_base))
         Bag.__init__(self, capacity, n_buckets=n_buckets, take_in_order=take_in_order, key=key)
         self.max_duration = max_duration if max_duration is not None else Config.max_duration
+        self.busyness = 0.5
 
     # def put(self, task: Task):
     #     return Bag.put(self, task, (hash(task), hash(task.stamp.evidential_base)))

pynars/NARS/DataStructures/_py/Memory.py

@@ -25,6 +25,10 @@ def __init__(self, capacity: int, n_buckets: int = None, take_in_order: bool = F
         self.concepts = Bag(capacity, n_buckets=n_buckets, take_in_order=take_in_order)
         self.output_buffer = output_buffer
 
+    @property
+    def busyness(self):
+        return self.concepts.busyness
+
     def accept(self, task: Task):
         '''
         **Accept task**: Accept a task from the `Overall Experience`, and link it from all directly related concepts. Ref: *The Conceptual Design of OpenNARS 3.1.0*.

pynars/Narsese/_py/Sentence.py

@@ -11,7 +11,6 @@
 
 from pynars.Config import Config, Enable
 from pynars import Global
-from ...NAL.Functions import F_expectation
 
 
 class Punctuation(Enum):