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unity-tech-cn:/develop/memorydump
unity-tech-cn:/develop/permutepytorch
unity-tech-cn:/develop/sac-targetq
unity-tech-cn:/develop/actions-out
unity-tech-cn:/develop/reshapeonnxmemories
unity-tech-cn:/develop/crawlergail
unity-tech-cn:/develop/debugtorchfood
unity-tech-cn:/develop/hybrid-actions
unity-tech-cn:/develop/bullet-hell
unity-tech-cn:/develop/action-spec-gym
unity-tech-cn:/develop/battlefoodcollector
unity-tech-cn:/develop/use-action-buffers
unity-tech-cn:/develop/hardswish
unity-tech-cn:/develop/leakyrelu
unity-tech-cn:/develop/torch-clip-scale
unity-tech-cn:/develop/contentropy
unity-tech-cn:/develop/manch
unity-tech-cn:/develop/torchcrawlerdebug
unity-tech-cn:/develop/fix-nan
unity-tech-cn:/develop/multitype-buffer
unity-tech-cn:/develop/windows-delay
unity-tech-cn:/develop/torch-tanh
unity-tech-cn:/develop/gail-norm
unity-tech-cn:/develop/multiprocess
unity-tech-cn:/develop/unified-obs
unity-tech-cn:/develop/rm-rf-new-models
unity-tech-cn:/develop/skipcritic
unity-tech-cn:/develop/centralizedcritic
unity-tech-cn:/develop/dodgeball-tests
unity-tech-cn:/develop/cc-teammanager
unity-tech-cn:/develop/weight-decay
unity-tech-cn:/develop/singular-embeddings
unity-tech-cn:/develop/zombieteammanager
unity-tech-cn:/develop/superpush
unity-tech-cn:/develop/teammanager
unity-tech-cn:/develop/zombie-exp
unity-tech-cn:/develop/update-readme
unity-tech-cn:/develop/readme-fix
unity-tech-cn:/develop/coma-noact
unity-tech-cn:/develop/coma-withq
unity-tech-cn:/develop/coma2
unity-tech-cn:/develop/action-slice
unity-tech-cn:/develop/gru
unity-tech-cn:/develop/critic-op-lstm-currentmem
unity-tech-cn:/develop/decaygail
unity-tech-cn:/develop/gail-srl-hack
unity-tech-cn:/develop/rear-pad
unity-tech-cn:/develop/mm-copyright-dates
unity-tech-cn:/develop/dodgeball-raycasts
unity-tech-cn:/develop/collab-envs-exp-ervin
unity-tech-cn:/develop/pushcollabonly
unity-tech-cn:/develop/sample-curation
unity-tech-cn:/develop/soccer-groupman
unity-tech-cn:/develop/input-actuator-tanks
unity-tech-cn:/develop/validate-release-fix
unity-tech-cn:/develop/new-console-log
unity-tech-cn:/develop/lex-walker-model
unity-tech-cn:/develop/lstm-burnin
unity-tech-cn:/develop/grid-vaiable-names
unity-tech-cn:/develop/fix-attn-embedding
unity-tech-cn:/develop/api-documentation-update-some-fixes
unity-tech-cn:/develop/update-grpc
unity-tech-cn:/develop/grid-rootref-debug
unity-tech-cn:/develop/pbcollab-rays
unity-tech-cn:/develop/2.0-verified-pre
unity-tech-cn:/develop/parameterizedenvs
unity-tech-cn:/develop/custom-ray-sensor
unity-tech-cn:/develop/mm-add-v2blog
unity-tech-cn:/develop/custom-raycast
unity-tech-cn:/develop/area-manager
unity-tech-cn:/develop/remove-unecessary-lr
unity-tech-cn:/develop/use-base-env-in-learn
unity-tech-cn:/soccer-fives/multiagent
unity-tech-cn:/develop/cubewars/splashdamage
unity-tech-cn:/develop/add-fire/exp
unity-tech-cn:/develop/add-fire/jit
unity-tech-cn:/develop/add-fire/speedtest
unity-tech-cn:/develop/add-fire/bc
unity-tech-cn:/develop/add-fire/ckpt-2
unity-tech-cn:/develop/add-fire/normalize-context
unity-tech-cn:/develop/add-fire/components-dir
unity-tech-cn:/develop/add-fire/halfentropy
unity-tech-cn:/develop/add-fire/memoryclass
unity-tech-cn:/develop/add-fire/categoricaldist
unity-tech-cn:/develop/add-fire/mm
unity-tech-cn:/develop/add-fire/sac-lst
unity-tech-cn:/develop/add-fire/mm3
unity-tech-cn:/develop/add-fire/continuous
unity-tech-cn:/develop/add-fire/ghost
unity-tech-cn:/develop/add-fire/policy-tests
unity-tech-cn:/develop/add-fire/export-discrete
unity-tech-cn:/develop/add-fire/test-simple-rl-fix-resnet
unity-tech-cn:/develop/add-fire/remove-currdoc
unity-tech-cn:/develop/add-fire/clean2
unity-tech-cn:/develop/add-fire/doc-cleanups
unity-tech-cn:/develop/add-fire/changelog
unity-tech-cn:/develop/add-fire/mm2
unity-tech-cn:/develop/model-transfer/add-physics
unity-tech-cn:/develop/model-transfer/train
unity-tech-cn:/develop/jit/experiments
unity-tech-cn:/exp-vince/sep30-2020
unity-tech-cn:/hh-develop-gridsensor-tests/static
unity-tech-cn:/develop/hybrid-actions/distlist
unity-tech-cn:/develop/bullet-hell/buffer
unity-tech-cn:/goal-conditioning/new
unity-tech-cn:/goal-conditioning/sensors-2
unity-tech-cn:/goal-conditioning/sensors-3-pytest-fix
unity-tech-cn:/goal-conditioning/grid-world
unity-tech-cn:/soccer-comms/disc
unity-tech-cn:/develop/centralizedcritic/counterfact
unity-tech-cn:/develop/centralizedcritic/mm
unity-tech-cn:/develop/centralizedcritic/nonego
unity-tech-cn:/develop/zombieteammanager/disableagent
unity-tech-cn:/develop/zombieteammanager/killfirst
unity-tech-cn:/develop/superpush/int
unity-tech-cn:/develop/superpush/branch-cleanup
unity-tech-cn:/develop/teammanager/int
unity-tech-cn:/develop/teammanager/cubewar-nocycle
unity-tech-cn:/develop/teammanager/cubewars
unity-tech-cn:/develop/superpush/int/hunter
unity-tech-cn:/goal-conditioning/new/allo-crawler
unity-tech-cn:/develop/coma2/clip
unity-tech-cn:/develop/coma2/singlenetwork
unity-tech-cn:/develop/coma2/samenet
unity-tech-cn:/develop/coma2/fixgroup
unity-tech-cn:/develop/coma2/samenet/sum
unity-tech-cn:/hh-develop-dodgeball/goy-input
unity-tech-cn:/develop/soccer-groupman/mod
unity-tech-cn:/develop/soccer-groupman/mod/hunter
unity-tech-cn:/develop/soccer-groupman/mod/hunter/cine
unity-tech-cn:/ai-hw-2021/tensor-applier
此合并请求有变更与目标分支冲突。
/docs/Migrating.md
/ml-agents/mlagents/trainers/trainer_controller.py
/ml-agents/mlagents/trainers/stats.py
/ml-agents/mlagents/trainers/ghost/trainer.py
/ml-agents/mlagents/trainers/behavior_id_utils.py
/ml-agents/mlagents/trainers/ppo/trainer.py
/ml-agents/mlagents/trainers/sac/trainer.py
/ml-agents/mlagents/trainers/trainer/trainer.py
/ml-agents/mlagents/trainers/tests/test_stats.py
/ml-agents/mlagents/trainers/ghost/controller.py
/config/trainer_config.yaml
/docs/Training-Self-Play.md
/ml-agents/mlagents/trainers/tests/test_ghost.py
/ml-agents/mlagents/trainers/tests/test_simple_rl.py
/ml-agents/mlagents/trainers/trainer_util.py
/ml-agents/mlagents/trainers/policy/tf_policy.py
5 次代码提交
main
...
develop/cubewars
作者 | SHA1 | 备注 | 提交日期 |
---|---|---|---|
Andrew Cohen | 3a1912c1 | raise warning when latest_model_ratio not btwn 0, 1 | 5 年前 |
Andrew Cohen | 573f80cd | added to mig doc/address comments | 5 年前 |
Andrew Cohen | 1b9c643b | Merge branch 'master' into self-play-mutex | 5 年前 |
Andrew Cohen | 691cf3ac | removed "unpredictable behavior" | 5 年前 |
Andrew Cohen | afc2c05b | modified doc to not include strikers vs goalie | 5 年前 |
共有 16 个文件被更改,包括 618 次插入 和 215 次删除
-
6config/trainer_config.yaml
-
98docs/Training-Self-Play.md
-
1docs/Migrating.md
-
18ml-agents/mlagents/trainers/stats.py
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52ml-agents/mlagents/trainers/behavior_id_utils.py
-
7ml-agents/mlagents/trainers/trainer_controller.py
-
7ml-agents/mlagents/trainers/ppo/trainer.py
-
5ml-agents/mlagents/trainers/sac/trainer.py
-
36ml-agents/mlagents/trainers/tests/test_ghost.py
-
55ml-agents/mlagents/trainers/tests/test_simple_rl.py
-
7ml-agents/mlagents/trainers/tests/test_stats.py
-
6ml-agents/mlagents/trainers/trainer_util.py
-
4ml-agents/mlagents/trainers/policy/tf_policy.py
-
5ml-agents/mlagents/trainers/trainer/trainer.py
-
434ml-agents/mlagents/trainers/ghost/trainer.py
-
92ml-agents/mlagents/trainers/ghost/controller.py
|
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from typing import Dict, NamedTuple |
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from typing import NamedTuple |
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from urllib.parse import urlparse, parse_qs |
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name_behavior_id: str |
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""" |
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BehaviorIdentifiers is a named tuple of the identifiers that uniquely distinguish |
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an agent encountered in the trainer_controller. The named tuple consists of the |
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fully qualified behavior name, the name of the brain name (corresponds to trainer |
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in the trainer controller) and the team id. In the future, this can be extended |
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to support further identifiers. |
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""" |
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|
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behavior_id: str |
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behavior_ids: Dict[str, int] |
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team_id: int |
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Parses a name_behavior_id of the form name?team=0¶m1=i&... |
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Parses a name_behavior_id of the form name?team=0 |
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This allows you to access the brain name and distinguishing identifiers |
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without parsing more than once. |
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This allows you to access the brain name and team id of an agent |
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ids: Dict[str, int] = {} |
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if "?" in name_behavior_id: |
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name, identifiers = name_behavior_id.rsplit("?", 1) |
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if "&" in identifiers: |
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list_of_identifiers = identifiers.split("&") |
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else: |
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list_of_identifiers = [identifiers] |
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|
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for identifier in list_of_identifiers: |
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key, value = identifier.split("=") |
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ids[key] = int(value) |
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else: |
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name = name_behavior_id |
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|
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parsed = urlparse(name_behavior_id) |
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name = parsed.path |
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ids = parse_qs(parsed.query) |
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team_id: int = 0 |
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if "team" in ids: |
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team_id = int(ids["team"][0]) |
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name_behavior_id=name_behavior_id, brain_name=name, behavior_ids=ids |
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behavior_id=name_behavior_id, brain_name=name, team_id=team_id |
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|
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|
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def create_name_behavior_id(name: str, team_id: int) -> str: |
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""" |
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Reconstructs fully qualified behavior name from name and team_id |
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:param name: brain name |
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:param team_id: team ID |
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:return: name_behavior_id |
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""" |
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return name + "?team=" + str(team_id) |
|
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from mlagents_envs.logging_util import get_logger |
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from typing import Deque, Dict |
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from collections import deque |
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from mlagents.trainers.ghost.trainer import GhostTrainer |
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|
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logger = get_logger(__name__) |
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|
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|
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class GhostController: |
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""" |
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GhostController contains a queue of team ids. GhostTrainers subscribe to the GhostController and query |
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it to get the current learning team. The GhostController cycles through team ids every 'swap_interval' |
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which corresponds to the number of trainer steps between changing learning teams. |
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The GhostController is a unique object and there can only be one per training run. |
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""" |
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|
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def __init__(self, maxlen: int = 10): |
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""" |
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Create a GhostController. |
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:param maxlen: Maximum number of GhostTrainers allowed in this GhostController |
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""" |
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|
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# Tracks last swap step for each learning team because trainer |
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# steps of all GhostTrainers do not increment together |
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self._queue: Deque[int] = deque(maxlen=maxlen) |
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self._learning_team: int = -1 |
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# Dict from team id to GhostTrainer for ELO calculation |
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self._ghost_trainers: Dict[int, GhostTrainer] = {} |
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|
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@property |
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def get_learning_team(self) -> int: |
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""" |
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Returns the current learning team. |
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:return: The learning team id |
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""" |
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return self._learning_team |
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|
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def subscribe_team_id(self, team_id: int, trainer: GhostTrainer) -> None: |
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""" |
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Given a team_id and trainer, add to queue and trainers if not already. |
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The GhostTrainer is used later by the controller to get ELO ratings of agents. |
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:param team_id: The team_id of an agent managed by this GhostTrainer |
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:param trainer: A GhostTrainer that manages this team_id. |
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""" |
|||
if team_id not in self._ghost_trainers: |
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self._ghost_trainers[team_id] = trainer |
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if self._learning_team < 0: |
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self._learning_team = team_id |
|||
else: |
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self._queue.append(team_id) |
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|
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def change_training_team(self, step: int) -> None: |
|||
""" |
|||
The current learning team is added to the end of the queue and then updated with the |
|||
next in line. |
|||
:param step: The step of the trainer for debugging |
|||
""" |
|||
self._queue.append(self._learning_team) |
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self._learning_team = self._queue.popleft() |
|||
logger.debug( |
|||
"Learning team {} swapped on step {}".format(self._learning_team, step) |
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) |
|||
|
|||
# Adapted from https://github.com/Unity-Technologies/ml-agents/pull/1975 and |
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# https://metinmediamath.wordpress.com/2013/11/27/how-to-calculate-the-elo-rating-including-example/ |
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# ELO calculation |
|||
# TODO : Generalize this to more than two teams |
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def compute_elo_rating_changes(self, rating: float, result: float) -> float: |
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""" |
|||
Calculates ELO. Given the rating of the learning team and result. The GhostController |
|||
queries the other GhostTrainers for the ELO of their agent that is currently being deployed. |
|||
Note, this could be the current agent or a past snapshot. |
|||
:param rating: Rating of the learning team. |
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:param result: Win, loss, or draw from the perspective of the learning team. |
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:return: The change in ELO. |
|||
""" |
|||
opponent_rating: float = 0.0 |
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for team_id, trainer in self._ghost_trainers.items(): |
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if team_id != self._learning_team: |
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opponent_rating = trainer.get_opponent_elo() |
|||
r1 = pow(10, rating / 400) |
|||
r2 = pow(10, opponent_rating / 400) |
|||
|
|||
summed = r1 + r2 |
|||
e1 = r1 / summed |
|||
|
|||
change = result - e1 |
|||
for team_id, trainer in self._ghost_trainers.items(): |
|||
if team_id != self._learning_team: |
|||
trainer.change_opponent_elo(change) |
|||
|
|||
return change |
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