def enacted_interaction(self, interaction, data):
# Post enacted interaction event
AppState.state.get_event_manager().post_event(
events.AgentEnactionEvent(self, interaction, -1))
self.interaction_memory.add_interaction_to_history(interaction)
print "%s - Enacted: %s" % (self.name, interaction)
def enacted_interaction(self, interaction, data):
# Learn interaction if it is not yet known
if interaction not in self.interaction_memory.get_primitive_interactions(
):
self.interaction_memory.add_interaction(interaction)
# Post enacted interaction event
AppState.state.get_event_manager().post_event(
events.AgentEnactionEvent(
self, interaction,
self.interaction_memory.get_valence(interaction)))
self.interaction_memory.add_interaction_to_history(interaction)
if not self.enacted == None:
self.learn_composite_interaction(self.enacted, interaction)
self.enacted = interaction
def enacted_interaction(self, interaction_, data):
self.enacting_interaction_step += 1
intended_primitive_interaction = data
self.enacted_sequence.append(interaction_)
# Learn interaction if it is not yet known
if interaction_ not in self.interaction_memory.get_primitive_interactions(
):
self.interaction_memory.add_interaction(interaction_)
# Post enacted interaction event
AppState.state.get_event_manager().post_event(
events.AgentEnactionEvent(
self, interaction_,
self.interaction_memory.get_valence(interaction_)))
self.interaction_memory.add_interaction_to_history(interaction_)
if (not interaction_ == intended_primitive_interaction
or self.enacting_interaction_step >= len(
self.enacting_interaction_sequence)):
# Failed or done enacting
self.enacting_interaction = False
# Reconstruct enacted interaction from hierarchy of intended
# interaction
enacted = self.intended_interaction.reconstruct_from_hierarchy(
self.enacted_sequence)
AppState.get_state().get_logger().info("%s - Enacted: %s" %
(self.name, enacted))
# Add the interaction as an alternative interaction if the intended interaction failed
if enacted != self.intended_interaction:
if self.interaction_memory.add_alternative_interaction(
self.intended_interaction, enacted):
AppState.get_state().get_logger().info(
"%s - Interaction added as alternative" % self.name)
# Step 5: add new or reinforce existing composite interactions
learned_or_reinforced = []
if isinstance(enacted, interaction.CompositeInteraction):
learned_or_reinforced.append(enacted)
if len(self.history) >= 1:
previous = self.history[-1]
# <interaction at t-1, enacted interaction>
t1enacted = interaction.CompositeInteraction(previous, enacted)
learned_or_reinforced.append(t1enacted)
if len(self.history) >= 2:
penultimate = self.history[-2]
# <interaction at t-2, interaction at t-1>
t2t1 = interaction.CompositeInteraction(
penultimate, previous)
# <<interaction at t-2, interaction at t-1>, enacted interaction>
t2t1_enacted = interaction.CompositeInteraction(
t2t1, enacted)
learned_or_reinforced.append(t2t1_enacted)
# <interaction at t-2, <interaction at t-1, enacted interaction>>
t2_t1enacted = interaction.CompositeInteraction(
penultimate, t1enacted)
learned_or_reinforced.append(t2_t1enacted)
for composite in learned_or_reinforced:
if composite not in self.interaction_memory.get_composite_interactions(
):
self.interaction_memory.add_interaction(composite)
else:
self.interaction_memory.increment_weight(composite)
# Keep history of last 100 actions performed
if len(self.history) > 100:
self.history.pop(0)
self.history.append(enacted)
"""
According to the paper:
for pre_interaction in self.context:
composite = interaction.CompositeInteraction(pre_interaction, enacted)
learned_or_reinforced.append(composite)
if composite not in self.interaction_memory.get_composite_interactions():
self.interaction_memory.add_interaction(composite)
else:
self.interaction_memory.increment_weight(composite)
"""
# Step 6: update context
self.update_context(enacted, learned_or_reinforced)
else:
# Not done
pass