Merge branch 'main' into unit_testing

.gitlab-ci.yml

@@ -14,8 +14,8 @@ build-job:       # This job runs in the build stage, which runs first.
   image: python:slim
   script:
     - echo "Compiling the code..."
-    - pip install -U twine
+    - pip install twine --upgrade
     - python setup.py sdist
     - echo "Compile complete."
-    - twine upload dist/*
+    - twine upload dist/* --username $USER_NAME --password $API_KEY --repository marl-factory-grid
     - echo "Upload complete."

marl_factory_grid/configs/default_config.yaml

@@ -22,13 +22,6 @@ Agents:
     - Inventory
     - DropOffLocations
     - Maintainers
-    # This is special for agents, as each one is differten and can act as an adversary e.g.
-    Positions:
-      - (16, 7)
-      - (16, 6)
-      - (16, 3)
-      - (16, 4)
-      - (16, 5)
 Entities:
   Batteries:
     initial_charge: 0.8

marl_factory_grid/configs/eight_puzzle.yaml

@@ -0,0 +1,55 @@
+Agents:
+  Wolfgang:
+    Actions:
+      - Noop
+      - Move4
+    Observations:
+      - Other
+      - Walls
+      - Destination
+    Clones:
+      - Juergen
+      - Soeren
+      - Walter
+      - Siggi
+      - Dennis
+      - Karl-Heinz
+      - Kevin
+    is_blocking_pos: true
+Entities:
+  Destinations:
+    # Let them spawn on closed doors and agent positions
+    ignore_blocking: true
+    # We need a special spawn rule...
+    spawnrule:
+      # ...which assigns the destinations per agent
+      SpawnDestinationsPerAgent:
+        # we use this parameter
+        coords_or_quantity:
+          # to enable and assign special positions per agent
+          Wolfgang: 1
+          Karl-Heinz: 1
+          Kevin: 1
+          Juergen: 1
+          Soeren: 1
+          Walter: 1
+          Siggi: 1
+          Dennis: 1
+General:
+  env_seed: 69
+  individual_rewards: true
+  level_name: eight_puzzle
+  pomdp_r: 3
+  verbose: True
+  tests: false
+
+Rules:
+  # Utilities
+  WatchCollisions:
+    done_at_collisions: false
+
+  # Done Conditions
+  DoneAtDestinationReach:
+    condition: simultanious
+  DoneAtMaxStepsReached:
+    max_steps: 500

marl_factory_grid/environment/factory.py

@@ -97,20 +97,26 @@ class Factory(gym.Env):
         return self.state.entities[item]
 
     def reset(self) -> (dict, dict):
+
+        # Reset information the state holds
+        self.state.reset()
+
+        # Reset Information the GlobalEntity collection holds.
         self.state.entities.reset()
 
         # All is set up, trigger entity spawn with variable pos
         self.state.rules.do_all_reset(self.state)
 
         # Build initial observations for all agents
-        return self.obs_builder.refresh_and_build_for_all(self.state)
+        self.obs_builder.reset(self.state)
+        return self.obs_builder.build_for_all(self.state)
 
     def manual_step_init(self) -> List[Result]:
         self.state.curr_step += 1
 
         # Main Agent Step
         pre_step_result = self.state.rules.tick_pre_step_all(self)
-        self.obs_builder.reset_struc_obs_block(self.state)
+        self.obs_builder.reset(self.state)
         return pre_step_result
 
     def manual_get_named_agent_obs(self, agent_name: str) -> (List[str], np.ndarray):
@@ -164,7 +170,7 @@ class Factory(gym.Env):
 
         info.update(step_reward=sum(reward), step=self.state.curr_step)
 
-        obs = self.obs_builder.refresh_and_build_for_all(self.state)
+        obs = self.obs_builder.build_for_all(self.state)
         return None, [x for x in obs.values()], reward, done, info
 
     def summarize_step_results(self, tick_results: list, done_check_results: list) -> (int, dict, bool):

marl_factory_grid/environment/groups/agents.py

@@ -1,6 +1,5 @@
 from marl_factory_grid.environment.entity.agent import Agent
 from marl_factory_grid.environment.groups.collection import Collection
-from marl_factory_grid.environment.rules import SpawnAgents
 
 
 class Agents(Collection):
@@ -8,7 +7,7 @@ class Agents(Collection):
 
     @property
     def spawn_rule(self):
-        return {SpawnAgents.__name__: {}}
+        return {}
 
     @property
     def var_is_blocking_light(self):

marl_factory_grid/environment/groups/global_entities.py

@@ -27,7 +27,7 @@ class Entities(Objects):
     @property
     def floorlist(self):
         shuffle(self._floor_positions)
-        return self._floor_positions
+        return [x for x in self._floor_positions]
 
     def __init__(self, floor_positions):
         self._floor_positions = floor_positions

marl_factory_grid/environment/rules.py

@@ -70,28 +70,22 @@ class SpawnAgents(Rule):
 
     def on_reset(self, state):
         agents = state[c.AGENT]
-        empty_positions = state.entities.empty_positions[:len(state.agents_conf)]
         for agent_name, agent_conf in state.agents_conf.items():
+            empty_positions = state.entities.empty_positions
             actions = agent_conf['actions'].copy()
             observations = agent_conf['observations'].copy()
             positions = agent_conf['positions'].copy()
             other = agent_conf['other'].copy()
-            if positions:
-                shuffle(positions)
-                while True:
-                    try:
-                        pos = positions.pop()
-                    except IndexError:
-                        raise ValueError(f'It was not possible to spawn an Agent on the available position: '
-                                         f'\n{agent_conf["positions"].copy()}')
-                    if bool(agents.by_pos(pos)) or not state.check_pos_validity(pos):
-                        continue
-                    else:
-                        agents.add_item(Agent(actions, observations, pos, str_ident=agent_name, **other))
-                    break
+
+            if position := h.get_first(x for x in positions if x in empty_positions):
+                assert state.check_pos_validity(position), 'smth went wrong....'
+                agents.add_item(Agent(actions, observations, position, str_ident=agent_name, **other))
+            elif positions:
+                raise ValueError(f'It was not possible to spawn an Agent on the available position: '
+                                 f'\n{agent_conf["positions"].copy()}')
             else:
                 agents.add_item(Agent(actions, observations, empty_positions.pop(), str_ident=agent_name, **other))
-        pass
+        return []
 
 
 class DoneAtMaxStepsReached(Rule):
@@ -103,7 +97,7 @@ class DoneAtMaxStepsReached(Rule):
     def on_check_done(self, state):
         if self.max_steps <= state.curr_step:
             return [DoneResult(validity=c.VALID, identifier=self.name)]
-        return [DoneResult(validity=c.NOT_VALID, identifier=self.name)]
+        return []
 
 
 class AssignGlobalPositions(Rule):
@@ -130,7 +124,7 @@ class WatchCollisions(Rule):
 
     def tick_post_step(self, state) -> List[TickResult]:
         self.curr_done = False
-        pos_with_collisions = state.get_all_pos_with_collisions()
+        pos_with_collisions = state.get_collision_positions()
         results = list()
         for pos in pos_with_collisions:
             guests = [x for x in state.entities.pos_dict[pos] if x.var_can_collide]

marl_factory_grid/levels/eight_puzzle.txt

@@ -0,0 +1,5 @@
+#####
+#---#
+#---#
+#---#
+#####

marl_factory_grid/modules/batteries/rules.py

@@ -60,7 +60,7 @@ class BatteryDecharge(Rule):
 
             batteries.by_entity(agent).decharge(energy_consumption)
 
-            results.append(TickResult(self.name, entity=agent, validity=c.VALID))
+            results.append(TickResult(self.name, entity=agent, validity=c.VALID, value=energy_consumption))
 
         return results
 

marl_factory_grid/modules/clean_up/rules.py

@@ -22,7 +22,7 @@ class DoneOnAllDirtCleaned(Rule):
     def on_check_done(self, state) -> [DoneResult]:
         if len(state[d.DIRT]) == 0 and state.curr_step:
             return [DoneResult(validity=c.VALID, identifier=self.name, reward=self.reward)]
-        return [DoneResult(validity=c.NOT_VALID, identifier=self.name)]
+        return []
 
 
 class RespawnDirt(Rule):
@@ -81,5 +81,6 @@ class EntitiesSmearDirtOnMove(Rule):
                     old_pos_dirt = next(iter(old_pos_dirt))
                     if smeared_dirt := round(old_pos_dirt.amount * self.smear_ratio, 2):
                         if state[d.DIRT].spawn(entity.pos, amount=smeared_dirt):
-                            results.append(TickResult(identifier=self.name, entity=entity, validity=c.VALID))
+                            results.append(TickResult(identifier=self.name, entity=entity,
+                                                      validity=c.VALID, value=smeared_dirt))
         return results

marl_factory_grid/modules/destinations/__init__.py

@@ -1,7 +1,4 @@
 from .actions import DestAction
 from .entitites import Destination
 from .groups import Destinations
-from .rules import (DoneAtDestinationReachAll,
-                    DoneAtDestinationReachAny,
-                    SpawnDestinationsPerAgent,
-                    DestinationReachReward)
+from .rules import (DoneAtDestinationReach, SpawnDestinationsPerAgent, DestinationReachReward)

marl_factory_grid/modules/destinations/entitites.py

@@ -54,3 +54,6 @@ class Destination(Entity):
 
     def mark_as_reached(self):
         self._was_reached = True
+
+    def unmark_as_reached(self):
+        self._was_reached = False

marl_factory_grid/modules/destinations/rules.py

@@ -9,6 +9,13 @@ from marl_factory_grid.environment import constants as c
 
 from marl_factory_grid.modules.destinations import constants as d
 from marl_factory_grid.modules.destinations.entitites import Destination
+from marl_factory_grid.utils.states import Gamestate
+
+
+ANY             = 'any'
+ALL             = 'all'
+SIMULTANOIUS    = 'simultanious'
+CONDITIONS =[ALL, ANY, SIMULTANOIUS]
 
 
 class DestinationReachReward(Rule):
@@ -48,9 +55,9 @@ class DestinationReachReward(Rule):
         return results
 
 
-class DoneAtDestinationReachAll(DestinationReachReward):
+class DoneAtDestinationReach(DestinationReachReward):
 
-    def __init__(self, reward_at_done=d.REWARD_DEST_DONE, **kwargs):
+    def __init__(self, condition='any', reward_at_done=d.REWARD_DEST_DONE, **kwargs):
         """
         This rule triggers and sets the done flag if ALL Destinations have been reached.
 
@@ -59,68 +66,79 @@ class DoneAtDestinationReachAll(DestinationReachReward):
         :type dest_reach_reward: float
         :param dest_reach_reward: Specify the reward, agents get when reaching a single destination.
         """
-        super(DoneAtDestinationReachAll, self).__init__(**kwargs)
+        super().__init__(**kwargs)
+        self.condition = condition
         self.reward = reward_at_done
+        assert condition in CONDITIONS
 
     def on_check_done(self, state) -> List[DoneResult]:
-        if all(x.was_reached() for x in state[d.DESTINATION]):
-            return [DoneResult(self.name, validity=c.VALID, reward=self.reward)]
-        return [DoneResult(self.name, validity=c.NOT_VALID)]
-
-
-class DoneAtDestinationReachAny(DestinationReachReward):
-
-    def __init__(self, reward_at_done=d.REWARD_DEST_DONE, **kwargs):
-        f"""
-        This rule triggers and sets the done flag if ANY Destinations has been reached.
-        !!! IMPORTANT: 'reward_at_done' is shared between the agents; 'dest_reach_reward' is bound to a specific one.
-                
-        :type reward_at_done: float
-        :param reward_at_done: Specifies the reward, all agent get, when any destinations has been reached. 
-                                Default {d.REWARD_DEST_DONE}
-        :type dest_reach_reward: float
-        :param dest_reach_reward: Specify a single agents reward forreaching a single destination. 
-                                   Default {d.REWARD_DEST_REACHED}
-        """
-        super(DoneAtDestinationReachAny, self).__init__(**kwargs)
-        self.reward = reward_at_done
-
-    def on_check_done(self, state) -> List[DoneResult]:
-        if any(x.was_reached() for x in state[d.DESTINATION]):
-            return [DoneResult(self.name, validity=c.VALID, reward=d.REWARD_DEST_REACHED)]
-        return []
+        if self.condition == ANY:
+            if any(x.was_reached() for x in state[d.DESTINATION]):
+                return [DoneResult(self.name, validity=c.VALID, reward=self.reward)]
+        elif self.condition == ALL:
+            if all(x.was_reached() for x in state[d.DESTINATION]):
+                return [DoneResult(self.name, validity=c.VALID, reward=self.reward)]
+        elif self.condition == SIMULTANOIUS:
+            if all(x.was_reached() for x in state[d.DESTINATION]):
+                return [DoneResult(self.name, validity=c.VALID, reward=self.reward)]
+            else:
+                for dest in state[d.DESTINATION]:
+                    if dest.was_reached():
+                        for agent in state[c.AGENT].by_pos(dest.pos):
+                            if dest.bound_entity:
+                                if dest.bound_entity == agent:
+                                    pass
+                                else:
+                                    dest.unmark_as_reached()
+                                    return [DoneResult(f'{dest}_unmarked_as_reached',
+                                                       validity=c.NOT_VALID, entity=dest)]
+                            else:
+                                pass
+        else:
+            raise ValueError('Check spelling of Parameter "condition".')
 
 
 class SpawnDestinationsPerAgent(Rule):
-    def __init__(self, coords_or_quantity: Dict[str, List[Tuple[int, int]]]):
+    def __init__(self, coords_or_quantity: Dict[str, List[Tuple[int, int] | int]]):
         """
         Special rule, that spawn distinations, that are bound to a single agent a fixed set of positions.
         Usefull for introducing specialists, etc. ..
 
         !!! This rule does not introduce any reward or done condition.
 
-        :type coords_or_quantity:  Dict[str, List[Tuple[int, int]]
         :param coords_or_quantity: Please provide a dictionary with agent names as keys; and a list of possible
                                      destiantion coords as value. Example: {Wolfgang: [(0, 0), (1, 1), ...]}
         """
         super(Rule, self).__init__()
-        self.per_agent_positions = {key: [ast.literal_eval(x) for x in val] for key, val in coords_or_quantity.items()}
+        self.per_agent_positions = dict()
+        for agent_name, value in coords_or_quantity.items():
+            if isinstance(value, int):
+                per_agent_d = {agent_name: value}
+            else:
+                per_agent_d = {agent_name: [ast.literal_eval(x) for x in value]}
+            self.per_agent_positions.update(**per_agent_d)
 
-    def on_reset(self, state, lvl_map):
-        for (agent_name, position_list) in self.per_agent_positions.items():
+    def on_reset(self, state: Gamestate):
+        for (agent_name, coords_or_quantity) in self.per_agent_positions.items():
             agent = h.get_first(state[c.AGENT], lambda x: agent_name in x.name)
             assert agent
-            position_list = position_list.copy()
+            if isinstance(coords_or_quantity, int):
+                position_list = state.entities.floorlist
+                pos_left_counter = coords_or_quantity
+            else:
+                position_list = coords_or_quantity.copy()
+                pos_left_counter = 1  # Find a better way to resolve this.
             shuffle(position_list)
-            while True:
+            while pos_left_counter:
                 try:
                     pos = position_list.pop()
                 except IndexError:
                     print(f"Could not spawn Destinations at: {self.per_agent_positions[agent_name]}")
                     print(f'Check your agent placement: {state[c.AGENT]} ... Exit ...')
-                    exit(9999)
+                    exit(-9999)
                 if (not pos == agent.pos) and (not state[d.DESTINATION].by_pos(pos)):
                     destination = Destination(pos, bind_to=agent)
+                    pos_left_counter -= 1
                     break
                 else:
                     continue

marl_factory_grid/modules/maintenance/rules.py

@@ -1,6 +1,5 @@
 from typing import List
 
-import marl_factory_grid.modules.maintenance.constants
 from marl_factory_grid.environment.rules import Rule
 from marl_factory_grid.utils.results import TickResult, DoneResult
 from marl_factory_grid.environment import constants as c
@@ -31,5 +30,5 @@ class DoneAtMaintainerCollision(Rule):
         for agent in agents:
             if agent.pos in m_pos:
                 done_results.append(DoneResult(entity=agent, validity=c.VALID, identifier=self.name,
-                                               reward=marl_factory_grid.modules.maintenance.constants.MAINTAINER_COLLISION_REWARD))
+                                               reward=M.MAINTAINER_COLLISION_REWARD))
         return done_results

marl_factory_grid/modules/zones/rules.py

@@ -43,9 +43,6 @@ class AgentSingleZonePlacement(Rule):
             agent.move(state[z.ZONES][z_idxs.pop()].random_pos, state)
         return []
 
-    def tick_step(self, state):
-        return []
-
 
 class IndividualDestinationZonePlacement(Rule):
 

marl_factory_grid/utils/config_parser.py

@@ -1,4 +1,5 @@
 import ast
+from collections import defaultdict
 
 from os import PathLike
 from pathlib import Path
@@ -24,13 +25,21 @@ class FactoryConfigParser(object):
         self.config_path = Path(config_path)
         self.custom_modules_path = Path(custom_modules_path) if custom_modules_path is not None else custom_modules_path
         self.config = yaml.safe_load(self.config_path.open())
+        self._n_abbr_dict = None
 
     def __getattr__(self, item):
         return self['General'][item]
 
     def _get_sub_list(self, primary_key: str, sub_key: str):
         return [{key: [s for k, v in val.items() if k == sub_key for s in v] for key, val in x.items()
-                 } for x in self.config[primary_key]]
+                 } for x in self.config.get(primary_key, [])]
+
+    def _n_abbr(self, n):
+        assert isinstance(n, int)
+        if self._n_abbr_dict is None:
+            self._n_abbr_dict = defaultdict(lambda: 'th', {1: 'st', 2: 'nd', 3: 'rd'})
+        return self._n_abbr_dict[n]
+
 
     @property
     def agent_actions(self):
@@ -145,11 +154,18 @@ class FactoryConfigParser(object):
             observations.extend(x for x in self.agents[name]['Observations'] if x != c.DEFAULTS)
             positions = [ast.literal_eval(x) for x in self.agents[name].get('Positions', [])]
             other_kwargs = {k: v for k, v in self.agents[name].items() if k not in
-                            ['Actions', 'Observations', 'Positions']}
+                            ['Actions', 'Observations', 'Positions', 'Clones']}
             parsed_agents_conf[name] = dict(
                 actions=parsed_actions, observations=observations, positions=positions, other=other_kwargs
                                             )
 
+            clones = self.agents[name].get('Clones', 0)
+            if clones:
+                if isinstance(clones, int):
+                    clones = [f'{name}_the_{n}{self._n_abbr(n)}' for n in range(clones)]
+                for clone in clones:
+                    parsed_agents_conf[clone] = parsed_agents_conf[name].copy()
+
         return parsed_agents_conf
 
     def load_env_rules(self) -> List[Rule]:

marl_factory_grid/utils/logging/envmonitor.py

@@ -58,3 +58,6 @@ class EnvMonitor(Wrapper):
             pickle.dump(self._monitor_df.reset_index(), f, protocol=pickle.HIGHEST_PROTOCOL)
         if auto_plotting_keys:
             plot_single_run(filepath, column_keys=auto_plotting_keys)
+
+    def report_possible_colum_keys(self):
+        print(self._monitor_df.columns)

marl_factory_grid/utils/observation_builder.py

@@ -24,11 +24,7 @@ class OBSBuilder(object):
             return 0
 
     def __init__(self, level_shape: np.size, state: Gamestate, pomdp_r: int):
-        self._curr_env_step = None
         self.all_obs = dict()
-        self.light_blockers = defaultdict(lambda: False)
-        self.positional = defaultdict(lambda: False)
-        self.non_positional = defaultdict(lambda: False)
         self.ray_caster = dict()
 
         self.level_shape = level_shape
@@ -37,13 +33,15 @@ class OBSBuilder(object):
         self.size = np.prod(self.obs_shape)
 
         self.obs_layers = dict()
-
-        self.reset_struc_obs_block(state)
         self.curr_lightmaps = dict()
+
         self._floortiles = defaultdict(list, {pos: [Floor(*pos)] for pos in state.entities.floorlist})
 
-    def reset_struc_obs_block(self, state):
-        self._curr_env_step = state.curr_step
+        self.reset(state)
+
+    def reset(self, state):
+        # Reset temporary information
+        self.curr_lightmaps = dict()
         # Construct an empty obs (array) for possible placeholders
         self.all_obs[c.PLACEHOLDER] = np.full(self.obs_shape, 0, dtype=float)
         # Fill the all_obs-dict with all available entities
@@ -52,7 +50,8 @@ class OBSBuilder(object):
 
     def observation_space(self, state):
         from gymnasium.spaces import Tuple, Box
-        obsn = self.refresh_and_build_for_all(state)
+        self.reset(state)
+        obsn = self.build_for_all(state)
         if len(state[c.AGENT]) == 1:
             space = Box(low=0, high=1, shape=next(x for x in obsn.values()).shape, dtype=np.float32)
         else:
@@ -60,14 +59,13 @@ class OBSBuilder(object):
         return space
 
     def named_observation_space(self, state):
-        return self.refresh_and_build_for_all(state)
+        self.reset(state)
+        return self.build_for_all(state)
 
-    def refresh_and_build_for_all(self, state) -> (dict, dict):
-        self.reset_struc_obs_block(state)
+    def build_for_all(self, state) -> (dict, dict):
         return {agent.name: self.build_for_agent(agent, state)[0] for agent in state[c.AGENT]}
 
-    def refresh_and_build_named_for_all(self, state) -> Dict[str, Dict[str, np.ndarray]]:
-        self.reset_struc_obs_block(state)
+    def build_named_for_all(self, state) -> Dict[str, Dict[str, np.ndarray]]:
         named_obs_dict = {}
         for agent in state[c.AGENT]:
             obs, names = self.build_for_agent(agent, state)
@@ -85,9 +83,6 @@ class OBSBuilder(object):
         pass
 
     def build_for_agent(self, agent, state) -> (List[str], np.ndarray):
-        assert self._curr_env_step == state.curr_step, (
-            "The observation objekt has not been reset this state! Call 'reset_struc_obs_block(state)'"
-        )
         try:
             agent_want_obs = self.obs_layers[agent.name]
         except KeyError:
@@ -166,7 +161,8 @@ class OBSBuilder(object):
                             raise ValueError(f'Max(obs.size) for {e.name}:  {obs[idx].size}, but was: {len(v)}.')
         if self.pomdp_r:
             try:
-                light_map = np.zeros(self.obs_shape)
+                light_map = self.curr_lightmaps.get(agent.name, np.zeros(self.obs_shape))
+                light_map[:] = 0.0
                 visible_floor = self.ray_caster[agent.name].visible_entities(self._floortiles, reset_cache=False)
 
                 for f in set(visible_floor):

marl_factory_grid/utils/plotting/plotting_utils.py

@@ -49,7 +49,7 @@ def prepare_plt(df, hue, style, hue_order):
     plt.close('all')
     sns.set(rc={'text.usetex': False}, style='whitegrid')
     lineplot = sns.lineplot(data=df, x='Episode', y='Score', hue=hue, style=style,
-                            ci=95, palette=PALETTE, hue_order=hue_order, )
+                            errorbar=('ci', 95), palette=PALETTE, hue_order=hue_order, )
     plt.legend(bbox_to_anchor=(1.02, 1), loc='upper left', borderaxespad=0)
     plt.tight_layout()
     # lineplot.set_title(f'{sorted(list(df["Measurement"].unique()))}')

marl_factory_grid/utils/states.py

@@ -8,7 +8,7 @@ import numpy as np
 from marl_factory_grid.algorithms.static.utils import points_to_graph
 from marl_factory_grid.environment import constants as c
 from marl_factory_grid.environment.entity.entity import Entity
-from marl_factory_grid.environment.rules import Rule
+from marl_factory_grid.environment.rules import Rule, SpawnAgents
 from marl_factory_grid.utils.results import Result, DoneResult
 from marl_factory_grid.environment.tests import Test
 from marl_factory_grid.utils.results import Result
@@ -32,18 +32,19 @@ class StepRules:
         self.rules.append(item)
         return True
 
-    def do_all_reset(self, state):
-        for rule in self.rules:
-            if rule_reset_printline := rule.on_reset(state):
-                state.print(rule_reset_printline)
-        return c.VALID
-
     def do_all_init(self, state, lvl_map):
         for rule in self.rules:
             if rule_init_printline := rule.on_init(state, lvl_map):
                 state.print(rule_init_printline)
         return c.VALID
 
+    def do_all_reset(self, state):
+        SpawnAgents().on_reset(state)
+        for rule in self.rules:
+            if rule_reset_printline := rule.on_reset(state):
+                state.print(rule_reset_printline)
+        return c.VALID
+
     def tick_step_all(self, state):
         results = list()
         for rule in self.rules:
@@ -91,6 +92,10 @@ class Gamestate(object):
         self._floortile_graph = None
         self.tests = StepTests(*tests)
 
+    def reset(self):
+        self.curr_step = 0
+        self.curr_actions = None
+
     def __getitem__(self, item):
         return self.entities[item]
 
@@ -201,7 +206,7 @@ class Gamestate(object):
                 results.extend(on_check_done_result)
         return results
 
-    def get_all_pos_with_collisions(self) -> List[Tuple[(int, int)]]:
+    def get_collision_positions(self) -> List[Tuple[(int, int)]]:
         """
         Returns a list positions [(x, y), ... ] on which collisions occur. This does not include agents,
         that were unable to move because their target direction was blocked, also a form of collision.

random_testrun.py

@@ -12,7 +12,7 @@ from marl_factory_grid.utils.tools import ConfigExplainer
 
 if __name__ == '__main__':
     # Render at each step?
-    render = False
+    render = True
     # Reveal all possible Modules (Entities, Rules, Agents[Actions, Observations], etc.)
     explain_config = False
     # Collect statistics?
@@ -29,7 +29,7 @@ if __name__ == '__main__':
         ce.save_all(run_path / 'all_out.yaml')
 
     # Path to config File
-    path = Path('marl_factory_grid/configs/narrow_corridor.yaml')
+    path = Path('marl_factory_grid/configs/eight_puzzle.yaml')
 
     # Env Init
     factory = Factory(path)
@@ -61,6 +61,10 @@ if __name__ == '__main__':
     if record:
         factory.save_records(run_path / 'test.pb')
     if plotting:
-        plot_single_run(run_path)
+        factory.report_possible_colum_keys()
+        plot_single_run(run_path, column_keys=['Global_DoneAtDestinationReachAll', 'step_reward',
+                                               'Agent[Karl-Heinz]_DoneAtDestinationReachAll',
+                                               'Agent[Wolfgang]_DoneAtDestinationReachAll',
+                                               'Global_DoneAtDestinationReachAll'])
 
     print('Done!!! Goodbye....')

setup.py

@@ -5,7 +5,7 @@ long_description = (this_directory / "README.md").read_text()
 
 
 setup(name='Marl-Factory-Grid',
-      version='0.1.2',
+      version='0.2.0',
       description='A framework to research MARL agents in various setings.',
       author='Steffen Illium',
       author_email='steffen.illium@ifi.lmu.de',