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Created with Raphaël 2.2.030Jul2928272625232219171412111087528Jun25241918171210129May15137230Apr2322191715141211109843227Mar2625212019181514131211109876543129Feb2827262523222120191615141312109876Update deterministic order generators and testsEnhance reach goal functionality with new configurationsAdd target ground type and enhance counter movementAdd deadly ground feature with new ground typesRename variables and update function names for clarityAdd Cooperative Cuisine introductory Jupyter notebookRefactor plate config initialization and add loggerUpdate file paths in package_files functionAdd dynamic package data inclusion for additional directoriesAdd package_data to include additional directoriesAdd new hook and environment configuration filesMerge remote-tracking branch 'origin/rl-bachelor-thesis' into rl-bachelor-thesisfiles are now only read when creating cooking taskStart handle active effects and clean up obsolete objectsRemoved unnecessary importsSepareted base agent from other agents, random and llm agent overwrite manage_tasks methodAgents can now detect when they cannot interact and stop interacting when it is finishedMerge branch 'dev' into 142-restructure-reinforcement-learning-files-2Implemented a steerable version of the environment for the user to test it out in the play_gym.py.Updated prompting strategy. Gpt4o seems to work best, although not good. Actually pretty bad :(Added first version of llm agent with gpt4o-miniAdded first version of llm agent with gpt4o-minifixed rendering not working on GPU clusterupdated config files for MARLBetter logging of item manipulations of playersupdated experiment.yamlImplemented two basic StateConverters and integrated them into the hydra config managementIntegrated hydra for reinforcement learning run management.updated layout, config for multi agent rlAdded support for HTTPS/SSL, makeing it possible to use the web-export on more then just localhostfixed agents not moving full blocksmade caching of recipe graph optional, added controlled player argument to get_state_image, miscmade specs unbatchedcontinued implementing multi agent envupdated specs, implemented _stepstarted implementing multi agent envAll logs, videos, models and wandb data is stored in the logs folder which is included in the gitignore and will therefore not be pushed.All logs, videos, models and wandb data is stored in the logs folder which is included in the gitignore and will therefore not be pushed.trigger PutMealOnPlateHookCallback when meal is directly placed from pot to plateAdapted config files to have one study with deterministic order and one with random order. In the argument_parser.py there is one argument to switch between both variants. Inserted a Study Config paragraph in the readme about that.