Fix deprecations, switch to NARpyn

README.md

@@ -5,14 +5,8 @@ This repository hosts both a library that facilitates interfacing OpenNARS for A
 a bunch of experiments using Griddly.
 
 ## Installation
-You need to have OpenNARS-For-Applications installed somewhere. It is expected that you will export a `NARS_HOME` environment
-variable to specify where it is built.
-
 The recommended way to install dependencies is with Poetry: `poetry install`. `poetry shell` will open a shell with the virtual environment activated.
 
-Additionally, dependencies are listed in the `env.yml` file, that can be used to create a Conda environment (might be outdated).
-`lock.yml` is a lock-file that you can use to make a reproducible environment, Conda might fail to create it though.
-
 [Griddly](https://github.com/Bam4d/Griddly) requires to install Vulkan SDK, refer to its README.
 
 Install in editable mode to your environment: `pip install -e .`

experiments/drunk_dwarf/curriculum_learning/curriculum-control.py

@@ -4,12 +4,12 @@
 
 import griddly  # noqa
 import gym
-import neptune.new as neptune
+import neptune
 from griddly import gd
+from narpyn.ona.nar import *
 
 from narca.agent import Runner
 from narca.drunk_dwarf import DrunkDwarfAgent
-from narca.nar import *
 from narca.utils import *
 
 # setup a logger for nars output

experiments/drunk_dwarf/curriculum_learning/curriculum-load-1.py

@@ -4,12 +4,12 @@
 
 import griddly  # noqa
 import gym
-import neptune.new as neptune
+import neptune
 from griddly import gd
+from narpyn.ona.nar import *
 
 from narca.agent import Runner
 from narca.drunk_dwarf import DrunkDwarfAgent
-from narca.nar import *
 from narca.utils import *
 
 # setup a logger for nars output

experiments/drunk_dwarf/curriculum_learning/curriculum-scratch-1.py

@@ -4,12 +4,12 @@
 
 import griddly  # noqa
 import gym
-import neptune.new as neptune
+import neptune
 from griddly import gd
+from narpyn.ona.nar import *
 
 from narca.agent import Runner
 from narca.drunk_dwarf import DrunkDwarfAgent
-from narca.nar import *
 from narca.utils import *
 
 # setup a logger for nars output

experiments/drunk_dwarf/demonstrate/drunk_dwarf.py

@@ -4,10 +4,10 @@
 import griddly  # noqa
 import gym
 from griddly import gd
+from narpyn.ona.nar import *
 
 from narca.agent import Runner
 from narca.drunk_dwarf import DrunkDwarfAgent
-from narca.nar import *
 from narca.utils import *
 
 # setup a logger for nars output

experiments/drunk_dwarf/extended_curriculum/drunk_dwarf.py

@@ -4,12 +4,12 @@
 
 import griddly  # noqa
 import gym
-import neptune.new as neptune
+import neptune
 from griddly import GymWrapperFactory, gd
+from narpyn.ona.nar import *
 
 from narca.agent import Runner
 from narca.drunk_dwarf import DrunkDwarfAgent
-from narca.nar import *
 from narca.utils import *
 
 # setup a logger for nars output

experiments/drunk_dwarf/main/drunk_dwarf.py

@@ -5,12 +5,12 @@
 
 import gym
 import hyperstate
-import neptune.new as neptune
+import neptune
 from griddly import gd
+from narpyn.ona.nar import *
 
 from narca.agent import Runner
 from narca.drunk_dwarf import DrunkDwarfAgent
-from narca.nar import *
 from narca.utils import *
 
 # setup a logger for nars output
@@ -54,7 +54,7 @@ def key_check(_, info) -> bool:
     logger.info("Run configuration: %s", config)
 
     neprun = (
-        neptune.init(
+        neptune.init_run(
             project=os.environ["NEPTUNE_PROJECT"],
             tags=[ENV_NAME, MAIN_TAG, f"difficulty:{config.difficulty_level}"],
         )
@@ -128,7 +128,7 @@ def key_check(_, info) -> bool:
     callbacks = []
     if neprun is not None:
         neprun["parameters"] = {
-            "goals": [g.symbol for g in goals],
+            "goals": str([g.symbol for g in goals]),
             "think_ticks": config.agent.think_ticks,
             "view_radius": config.agent.view_radius,
             "num_episodes": config.num_episodes,

experiments/drunk_dwarf/main/random_agent.py

@@ -3,11 +3,11 @@
 
 import griddly  # noqa
 import gym
-import neptune.new as neptune
+import neptune
 from griddly import gd
+from narpyn.ona.nar import *
 
 from narca.drunk_dwarf import DrunkDwarfRandom
-from narca.nar import *
 from narca.utils import *
 
 # setup a logger for nars output

experiments/zelda/demonstrate/nars_zelda.py

@@ -6,8 +6,8 @@
 import gym
 import pexpect
 from griddly import gd
+from narpyn.ona.nar import *
 
-from narca.nar import *
 from narca.utils import *
 from narca.zelda import Runner, ZeldaAgent, ZeldaLevelGenerator
 

experiments/zelda/main/nars_zelda.py

@@ -4,11 +4,11 @@
 
 import griddly  # noqa
 import gym
-import neptune.new as neptune
+import neptune
 from griddly import gd
+from narpyn.ona.nar import *
 
 from narca.agent import Runner
-from narca.nar import *
 from narca.utils import *
 from narca.zelda import ZeldaAgent
 

experiments/zelda/procgen/nars_zelda.py

@@ -6,8 +6,8 @@
 import gym
 import pexpect
 from griddly import gd
+from narpyn.ona.nar import *
 
-from narca.nar import *
 from narca.utils import *
 from narca.zelda import Runner, ZeldaAgent, ZeldaLevelGenerator
 

narca/agent.py

@@ -7,10 +7,10 @@
 import numpy as np
 from griddly import gd
 from griddly.util.rllib.environment.level_generator import LevelGenerator
+from narpyn.ona.nar import get_raw_output, send_input, setup_nars
+from narpyn.ona.narsese import Goal, nal_now
 from tensorboardX import SummaryWriter
 
-from .nar import get_raw_output, send_input, setup_nars
-from .narsese import Goal, nal_now
 from .utils import NARS_PATH
 
 

narca/drunk_dwarf.py

@@ -4,10 +4,10 @@
 
 import gym
 import numpy as np
+from narpyn.ona.nar import *
 
 from .agent import Agent, NarsAgent
 from .astar import pathfind
-from .nar import *
 from .utils import *
 
 
@@ -227,19 +227,19 @@ def obj_label(obj_type: str, obloc: tuple[int, int]) -> Optional[str]:
                 ]
             )
 
-        obj_concurrent_belief = (
-            f"({obj_labels[0]} &| {obj_labels[1]})"
-            if len(obj_labels) > 1
-            else obj_labels[0]
-        )
-        if len(obj_labels) > 2:
-            for i in range(2, len(obj_labels)):
-                obj_concurrent_belief = f"({obj_concurrent_belief} &| {obj_labels[i]})"
+        # obj_concurrent_belief = (
+        #     f"({obj_labels[0]} &| {obj_labels[1]})"
+        #     if len(obj_labels) > 1
+        #     else obj_labels[0]
+        # )
+        # if len(obj_labels) > 2:
+        #     for i in range(2, len(obj_labels)):
+        #         obj_concurrent_belief = f"({obj_concurrent_belief} &| {obj_labels[i]})"
 
         # nal_now("<" + " &| ".join(obj_labels) + ">")
         # ic(obj_concurrent_belief)
-        self._send_beliefs([nal_now(obj_concurrent_belief)])
-        num_sent_beliefs += 1
+        # self._send_beliefs([nal_now(obj_concurrent_belief)])
+        # num_sent_beliefs += 1
 
         # try:
         #     avatar = next(
@@ -301,10 +301,13 @@ def obj_label(obj_type: str, obloc: tuple[int, int]) -> Optional[str]:
 
         # num_sent_beliefs += len(pos_beliefs) + len(diff_beliefs)
         # self._send_beliefs(pos_beliefs + diff_beliefs)
+        blfs = [nal_now(obj) for obj in obj_labels]
+        self._send_beliefs(blfs)
+        num_sent_beliefs = len(blfs)
         # ic("Sent pos beliefs:", pos_beliefs)
         # ic("Sent diff beliefs:", diff_beliefs)
         ic("Total beliefs sent:", num_sent_beliefs)
-        # sleep(1)
+        sleep(1)
 
 
 class DrunkDwarfRandom(Agent):