ReinforcementLearning.jl Files

ReinforcementLearningFarm ReinforcementLearningFarm-v0.0.3

Merged pull requests: - Fix deprecations (#10) (@femtocleaner[bot]) - implement epsilon-greedy policy with parametric type (#12) (@jbrea) - improve docs (#13) (@jbrea) - refactor policies (#15) (@jbrea) - Add ReinforcementLearningBase as dependent (#16) (@jbrea) - fix examples (#18) (@jbrea) - refactor existing components (#26) (@findmyway) - Prioritized dqn (#29) (@findmyway) - add double dqn (#30) (@findmyway) - add rainbow (#31) (@findmyway) - use new api in ReinforcementLearningEnvironments.jl (#33) (@findmyway) - bugfix and api simplification (#34) (@findmyway) - Switch Tracker.jl to Zygote.jl (#37) (@findmyway) - Support both Knet and Flux(with Zygote) (#38) (@findmyway) - add docs (#39) (@findmyway) - export AbstractActionSelector and add more comments (#42) (@findmyway) - Refactor buffer (#45) (@findmyway) - fix example in doc && update examples (#46) (@findmyway) - fix a performance bug in rainbow (#47) (@findmyway) - update dependencies (#48) (@findmyway) - update dependencies and docs (#49) (@findmyway) - update benchmark for circular_array_buffer (#50) (@findmyway) - Install TagBot as a GitHub Action (#53) (@JuliaTagBot) - clean up code (#54) (@findmyway) - add compat (#55) (@findmyway) - CompatHelper: add new compat entry for "Reexport" at version "0.2" (#56) (@github-actions[bot]) - add documentation stage in travis (#57) (@findmyway) - Add doc in travis (#58) (@findmyway) - Fix link in docs/src/index.md (#60) (@amanbh) - Update doc (#61) (@findmyway) - Update README.md & website link (#70) (@findmyway) - Update dependency (#78) (@findmyway) - MassInstallAction: Install the CompatHelper workflow on this repository (#99) (@findmyway) - CompatHelper: bump compat for "Reexport" to "1.0" (#172) (@github-actions[bot]) - update dependency (#177) (@findmyway) - Add Dockerfile (#187) (@findmyway) - Update readme (#188) (@findmyway) - docs: add findmyway as a contributor (#189) (@allcontributors[bot]) - docs: add drozzy as a contributor (#195) (@allcontributors[bot]) - docs: add rcnlee as a contributor (#199) (@allcontributors[bot]) - docs: add norci as a contributor (#200) (@allcontributors[bot]) - docs: add xiruizhao as a contributor (#203) (@allcontributors[bot]) - docs: add metab0t as a contributor (#204) (@allcontributors[bot]) - docs: add albheim as a contributor (#207) (@allcontributors[bot]) - docs: add michelangelo21 as a contributor (#214) (@allcontributors[bot]) - docs: add pilgrimygy as a contributor (#216) (@allcontributors[bot]) - docs: add Mobius1D as a contributor (#218) (@allcontributors[bot]) - docs: add ilancoulon as a contributor (#224) (@allcontributors[bot]) - docs: add pilgrimygy as a contributor (#230) (@allcontributors[bot]) - docs: add JinraeKim as a contributor (#243) (@allcontributors[bot]) - Prepare v0.9 (#252) (@findmyway) - docs: add luigiannelli as a contributor (#254) (@allcontributors[bot]) - docs: add JBoerma as a contributor (#255) (@allcontributors[bot]) - CompatHelper: bump compat for "ReinforcementLearningEnvironments" to "0.5" (#260) (@github-actions[bot]) - Fix inconsitencies in wrappers (#263) (@albheim) - setup CI for each subpackages (#264) (@findmyway) - Fix atari experiments (#265) (@Mobius1D) - Add timeperstep hook to qrdqn to fix test error (#266) (@albheim) - Update Flux version (#267) (@findmyway) - Setup docs generation pipeline (#269) (@findmyway) - Misc doc related fixes (#270) (@findmyway) - Update README.md (#271) (@findmyway) - docs: add JinraeKim as a contributor (#272) (@allcontributors[bot]) - Improve docs GitHub action (#273) (@findmyway) - Fix docs pipeline (#275) (@findmyway) - update readme (#276) (@findmyway) - CompatHelper: add new compat entry for "UnicodePlots" at version "1.3" for package ReinforcementLearningCore (#277) (@github-actions[bot]) - CompatHelper: bump compat for "Distributions" to "0.25" for package ReinforcementLearningCore (#278) (@github-actions[bot]) - CompatHelper: bump compat for "Distributions" to "0.25" for package ReinforcementLearningZoo (#279) (@github-actions[bot]) - docs: add plu70n as a contributor (#282) (@allcontributors[bot]) - Fix bug in CI (#283) (@findmyway) - Use Weave.jl to generate RLExperiments (#284) (@findmyway) - QRDQN experiment reproducibility fix (#294) (@ashwani-rathee) - Add Manifest.toml (#295) (@findmyway) - docs: add ashwani-rathee as a contributor (#296) (@allcontributors[bot]) - Add basic doc structure (#300) (@findmyway) - Update guide (#302) (@findmyway) - Update experiments (#303) (@findmyway) - fix figs (#304) (@findmyway) - Fix some simple experiments (#308) (@findmyway) - add plotting for cartpole and mountaincar with Plots.jl (#309) (@jamblejoe) - Remove GR in RLEnvs (#310) (@findmyway) - docs: add jamblejoe as a contributor (#311) (@allcontributors[bot]) - Add compat of Distributions@v0.24 in ReinforcementLearningExperiments (#312) (@findmyway) - Add example of SimplexSpace (#313) (@findmyway) - Improve tutorial (#314) (@findmyway) - Fix Atari related experiments (#315) (@findmyway) - CompatHelper: add new compat entry for "ImageTransformations" at version "0.8" for package ReinforcementLearningExperiments (#317) (@github-actions[bot]) - CompatHelper: add new compat entry for "ArcadeLearningEnvironment" at version "0.2" for package ReinforcementLearningExperiments (#318) (@github-actions[bot]) - CompatHelper: add new compat entry for "CUDA" at version "3" for package ReinforcementLearningExperiments (#319) (@github-actions[bot]) - update tips (#321) (@findmyway) - CompatHelper: bump compat for "GPUArrays" to "7" for package ReinforcementLearningCore (#322) (@github-actions[bot]) - docs: add albheim as a contributor for doc (#323) (@allcontributors[bot]) - Fix broken test (#325) (@Mobius1D) - Add a warning in docstring of state (#327) (@findmyway) - Update doc string of PrioritizedDQNLearner (#329) (@findmyway) - Expand DDPG to multi action spaces (#330) (@Mobius1D) - CompatHelper: bump compat for "StructArrays" to "0.6" for package ReinforcementLearningZoo (#331) (@github-actions[bot]) - fix 332 (#333) (@findmyway) - correct spelling in FAQ (#334) (@ultradian) - docs: add ultradian as a contributor for doc (#335) (@allcontributors[bot]) - fix typo (#338) (@findmyway) - docs: add eltociear as a contributor for doc (#339) (@allcontributors[bot]) - CompatHelper: bump compat for "FillArrays" to "0.12" for package ReinforcementLearningCore (#340) (@github-actions[bot]) - Add copyto function (#345) (@pilgrimygy) - add Base.:(==) and Base.hash for AbstractEnv and test nash_conv on KuhnPokerEnv (#348) (@peterchen96) - Fix legal_actions_mask indexing error in CircularSLART (#350) (@findmyway) - bump version of RLCore (#351) (@findmyway) - bump version of RLBae (#352) (@findmyway) - add LICENSE in RLBase (#353) (@findmyway) - bump version of RLZoo (#355) (@findmyway) - docs: add 00krishna as a contributor for bug (#356) (@allcontributors[bot]) - Add the tuning entropy component (#365) (@pilgrimygy) - Make general components (#370) (@pilgrimygy) - add weighted_softmax_explorer in the explorers.jl (#382) (@peterchen96) - Supplement functions in ReservoirTrajectory and BehaviorCloningPolicy (#390) (@peterchen96) - Update Flux version (#391) (@findmyway) - AddSequentialEnv (#394) (@findmyway) - Throw error in MultiAgentManager if it is applied to a SIMULTANEOUS env (#395) (@findmyway) - docs: add pkienscherf as a contributor for bug (#396) (@allcontributors[bot]) - Implementation of NFSP and NFSP_KuhnPoker experiment (#402) (@peterchen96) - Updated RLDatasets.jl (#403) (@Mobius1D) - Gym d4rl extension (#405) (@Mobius1D) - updates as per GridWorlds v0.5.0 (#406) (@Sid-Bhatia-0) - Reduce allocations and update docstring for GaussianNetwork (#414) (@albheim) - Fix a bug (#415) (@pilgrimygy) - Expand to d4rl-pybullet (#416) (@Mobius1D) - docs: add pilgrimygy as a contributor for bug (#417) (@allcontributors[bot]) - Fix 418 (#420) (@findmyway) - docs: add Krastanov as a contributor for doc (#422) (@allcontributors[bot]) - Make SAC policy use internal rng (#423) (@albheim) - Add wrapped_env[!] to access env inside wrappers (#426) (@albheim) - add stock trading env (#428) (@findmyway) - Add Atari datasets released by Google Research (#429) (@Mobius1D) - add kwargs to plot(env::) (#430) (@jamblejoe) - Unify parameter names (#437) (@pilgrimygy) - docs: add albheim as a contributor for maintenance (#438) (@allcontributors[bot]) - correct nfsp implementation (#439) (@peterchen96) - update the nfsp experiment's parameters (#440) (@peterchen96) - Tiny text typo (#441) (@Nthman) - docs: add LaarsOman as a contributor for doc (#442) (@allcontributors[bot]) - Add pre-train step; VAE component; CRR and PLAS algorithms (#443) (@pilgrimygy) - add MADDPG algorithm (#444) (@peterchen96) - add_Graph_Shortest_Path (#445) (@findmyway) - try to fix bugs of ActionTransformedEnv (#447) (@peterchen96) - Update report (#448) (@pilgrimygy) - Summer ospp project 210370190 mid-term report (#449) (@peterchen96) - add maxdepth kwarg to remove print_tree() deprecation warning (#450) (@burmecia) - docs: add burmecia as a contributor for code (#451) (@allcontributors[bot]) - RL unplugged implementation with tests (#452) (@Mobius1D) - Update report (#453) (@Mobius1D) - disable notebook generation (#454) (@johnnychen94) - Revert "Update report" (#456) (@findmyway) - Update report (#457) (@pilgrimygy) - fix installation docs (#458) (@Mobius1D) - docs: add peterchen96 as a contributor for code, doc (#459) (@allcontributors[bot]) - Create LICENSE (#461) (@Mobius1D) - Add docs (#462) (@Mobius1D) - Fix make.jl (#463) (@Mobius1D) - Delete LICENSE (#465) (@Mobius1D) - fix CI (#466) (@findmyway) - Fix RLDatasets.jl documentation (#467) (@Mobius1D) - update report (#468) (@peterchen96) - Fix ci (#469) (@Mobius1D) - Update maddpg and the report (#470) (@peterchen96) - Report (#474) (@pilgrimygy) - Control whether run displays description of experiment (#477) (@ShuhuaGao) - docs: add ShuhuaGao as a contributor for code, question (#478) (@allcontributors[bot]) - Chancestyle doc update (#479) (@ShuhuaGao) - FisherBRC algorithm and update docs (#480) (@pilgrimygy) - Add the experiment of MADDPG. (#481) (@peterchen96) - Add bsuite datasets (#482) (@Mobius1D) - update report and add reward bonus (#483) (@pilgrimygy) - Update manifest (#484) (@Mobius1D) - add GPU support for GaussianNetwork, fix [#455] (#486) (@burmecia) - Update experiments of maddpg (#487) (@peterchen96) - ?Update prob function of QBasedPolicy. (#488) (@peterchen96) - Update report. (#489) (@peterchen96) - Fix gsutil for windows and fix docs (#491) (@Mobius1D) - add vmpo algorithm (#492) (@burmecia) - update vae (#494) (@pilgrimygy) - Add dm datasets (#495) (@Mobius1D) - Play OpenSpiel envs with NFSP and try to add ED algorithm. (#496) (@peterchen96) - fix bug (#497) (@pilgrimygy) - Update BEAR algorithm (#498) (@pilgrimygy) - More efficient float32 randn (#499) (@albheim) - Add support for deep ope in RLDatasets.jl (#500) (@Mobius1D) - update BCQ (#501) (@pilgrimygy) - update discrete BCQ (#502) (@pilgrimygy) - update offline RL experiment (#507) (@pilgrimygy) - Update ED algorithm and the report. (#508) (@peterchen96) - cpu and gpu test (#509) (@pilgrimygy) - Fix dispatch for is_discrete_space (#510) (@johannes-fischer) - docs: add johannes-fischer as a contributor for code (#511) (@allcontributors[bot]) - update report (#512) (@pilgrimygy) - update report (#513) (@peterchen96) - Fix random net init in sac example (#514) (@albheim) - WIP to implement FQE (#515) (@Mobius1D) - OSPP Report for RLDatasets.jl (#516) (@Mobius1D) - Update report (#518) (@Mobius1D) - Update reward wrappers to be more consistent (#519) (@albheim) - fixed findmax unconsistency (#521) (@3rdCore) - docs: add 3rdCore as a contributor for bug, code (#522) (@allcontributors[bot]) - close [#493] (#523) (@findmyway) - Update compat & version (#524) (@findmyway) - Fix rlexps (#525) (@findmyway) - Bump rlenvs (#526) (@findmyway) - close [#527] (#528) (@bhatiaabhinav) - docs: add bhatiaabhinav as a contributor for bug, code (#529) (@allcontributors[bot]) - Refine the doc and make minor changes of TabularApproximator (#532) (@ShuhuaGao) - Fix bug in MaskedPPOTrajectory (#533) (@findmyway) - bugfix with ZeroTo (#534) (@findmyway) - Revert unexpected change in PPO (#535) (@findmyway) - Fix 530 (#536) (@findmyway) - Improves plotting for classical control experiments (#537) (@harwiltz) - Fix rldatasets (#538) (@findmyway) - docs: add harwiltz as a contributor for code, doc (#539) (@allcontributors[bot]) - Bump version (#540) (@findmyway) - fix RLIntro#63 (#541) (@findmyway) - fix RLIntro#64 (#542) (@findmyway) - Added a continuous option for CartPoleEnv (#543) (@dylan-asmar) - docs: add dylan-asmar as a contributor for code (#544) (@allcontributors[bot]) - Bump version (#545) (@findmyway) - Fix bug in cart pole float32 (#547) (@findmyway) - Update links to RLIntro (#548) (@findmyway) - Make experiments GPU compatible (#549) (@findmyway) - Add compat (#550) (@findmyway) - Bugfix with cart pole env (#552) (@findmyway) - make bc gpu compatable (#553) (@findmyway) - docs: add andreyzhitnikov as a contributor for bug (#554) (@allcontributors[bot]) - Small typo (#555) (@kir0ul) - docs: add kir0ul as a contributor for doc (#556) (@allcontributors[bot]) - Fix/rand dummy action (#559) (@mo8it) - Fix warning about kwargs.data (#560) (@mo8it) - docs: add Mo8it as a contributor for code (#561) (@allcontributors[bot]) - Fix dummy action for continuous action spaces (#562) (@mo8it) - Fix/rand interval (#563) (@mo8it) - Remove unneeded method (#564) (@mo8it) - Fix typo in ospp_final_term_report_210370741/index.md (#565) (@eltociear) - Fix 566 (#567) (@findmyway) - Fix documentation for environments (#570) (@blegat) - docs: add blegat as a contributor for doc (#571) (@allcontributors[bot]) - fix [#569] (#573) (@findmyway) - CompatHelper: bump compat for "ArrayInterface" to "4" for package ReinforcementLearningCore (#574) (@github-actions[bot]) - bump version of RLCore and RLZoo (#576) (@findmyway) - Update EpsilonGreedyExplorer example (#577) (@kir0ul) - CompatHelper: bump compat for "FillArrays" to "0.13" for package ReinforcementLearningCore (#583) (@github-actions[bot]) - Default qnetwork initializer (#586) (@HenriDeh) - docs: add HenriDeh as a contributor for code, doc (#587) (@allcontributors[bot]) - using act_limit parameter in target_actor (#588) (@NPLawrence) - docs: add NPLawrence as a contributor for code (#589) (@allcontributors[bot]) - CompatHelper: bump compat for "ArrayInterface" to "5" for package ReinforcementLearningCore (#590) (@github-actions[bot]) - Fix documentation typo (#591) (@kir0ul) - Fixing and generalizing GaussianNetwork (#592) (@HenriDeh) - Fix typos in docs (#593) (@bileamScheuvens) - docs: add bileamScheuvens as a contributor for doc (#594) (@allcontributors[bot]) - Add CovGaussianNetwork to work with covariance (#597) (@HenriDeh) - Fixing Gaussian Network gradient (#598) (@HenriDeh) - Update Supporting (#599) (@findmyway) - docs: add harwiltz as a contributor for bug (#601) (@allcontributors[bot]) - Rewrite initialization of StackFrames (#602) (@findmyway) - fix test logdetLorU with Float64 (#603) (@HenriDeh) - WIP: Add MPO in zoo (#604) (@HenriDeh) - fix [#605] (#606) (@findmyway) - docs: add jarbus as a contributor for bug (#607) (@allcontributors[bot]) - Add a reward normalizer (#609) (@HenriDeh) - Episode reset condition (#621) (@HenriDeh) - cspell add Optimise (#622) (@HenriDeh) - Add a categorical Network (#625) (@HenriDeh) - write doc (#627) (@HenriDeh) - fix [#624] (#628) (@findmyway) - docs: add tyleringebrand as a contributor for bug (#629) (@allcontributors[bot]) - Update How_to_implement_a_new_algorithm.md (#630) (@HenriDeh) - add a new notebook (#631) (@findmyway) - Use Trajectories.jl instead (#632) (@findmyway) - created fallback implementation for legal_action_space_mask (#644) (@baedan) - update node version (#645) (@findmyway) - docs: add baedan as a contributor for code (#646) (@allcontributors[bot]) - Tag the latest code as v0.10.1 (#647) (@findmyway) - added basic doc for TDLearner (#649) (@baedan) - Add JuliaRL_DQN_CartPole (#650) (@findmyway) - enable OpenSpiel (#691) (@findmyway) - Small improvements for TicTacToeEnv (#692) (@jonathan-laurent) - Update the "how to implement a new algorithm" (#695) (@HenriDeh) - Fix typo in algorithm implementation docs (#697) (@mplemay) - add PrioritizedDQN (#698) (@findmyway) - add QRDQN (#699) (@findmyway) - add REMDQN (#708) (@findmyway) - add IQN (#710) (@findmyway) - checkin Mainifest.toml (#711) (@findmyway) - CompatHelper: bump compat for "ReinforcementLearningCore" to "0.8" (#712) (@github-actions[bot]) - CompatHelper: bump compat for "ReinforcementLearningEnvironments" to "0.6" (#713) (@github-actions[bot]) - CompatHelper: bump compat for "ReinforcementLearningZoo" to "0.5" (#714) (@github-actions[bot]) - CompatHelper: bump compat for "AbstractTrees" to "0.4" for package ReinforcementLearningBase (#715) (@github-actions[bot]) - CompatHelper: bump compat for "Functors" to "0.3" for package ReinforcementLearningCore (#717) (@github-actions[bot]) - CompatHelper: bump compat for "UnicodePlots" to "3" for package ReinforcementLearningCore (#718) (@github-actions[bot]) - CompatHelper: bump compat for "ReinforcementLearningCore" to "0.8" for package ReinforcementLearningZoo (#720) (@github-actions[bot]) - CompatHelper: bump compat for "Functors" to "0.3" for package ReinforcementLearningZoo (#721) (@github-actions[bot]) - CompatHelper: add new compat entry for "StableRNGs" at version "1" for package ReinforcementLearningExperiments (#722) (@github-actions[bot]) - CompatHelper: bump compat for "ReinforcementLearning" to "0.10" for package ReinforcementLearningExperiments (#723) (@github-actions[bot]) - add rainbow (#724) (@findmyway) - Adapted SAC to support MultiThreadedEnv (#726) (@BigFood2307) - Add the number of episodes (#727) (@ll7) - docs: add ll7 as a contributor for doc (#728) (@allcontributors[bot]) - Add struct view (#732) (@findmyway) - add VPG (#733) (@findmyway) - CompatHelper: add new compat entry for "Distributions" at version "0.25" for package ReinforcementLearningZoo (#734) (@github-actions[bot]) - CompatHelper: add new compat entry for "Distributions" at version "0.25" for package ReinforcementLearningExperiments (#735) (@github-actions[bot]) - fixed hyperlink in readme (#742) (@mplemay) - docs: add mplemay as a contributor for doc (#743) (@allcontributors[bot]) - Create FUNDING.yml (#746) (@findmyway) - TRPO (#747) (@baedan) - CompatHelper: bump compat for "CommonRLSpaces" to "0.2" for package ReinforcementLearningBase (#748) (@github-actions[bot]) - Fix parameter names for AsyncTrajectoryStyle (#749) (@ludvigk) - Update DoEveryNEpisode hook to new api (#750) (@ludvigk) - docs: add ludvigk as a contributor for code (#751) (@allcontributors[bot]) - Update TwinNetwork (#752) (@ludvigk) - Typo in hooks docs (#754) (@kir0ul) - CommonRLSpace -> DomainSets (#756) (@findmyway) - Fix typo (#767) (@jeremiahpslewis) - Fix typo (#768) (@jeremiahpslewis) - Fix TD Learner so that it handles MultiAgent/Simultaneous with NoOp (#769) (@jeremiahpslewis) - Bump RLBase compat to 0.11 (#771) (@HenriDeh) - Remove manifest from the repo (#773) (@HenriDeh) - import params and gradient (#774) (@HenriDeh) - fix compat (#775) (@HenriDeh) - Trying to reimplement experiments (#776) (@HenriDeh) - Add a developer mode (#777) (@HenriDeh) - added pettingzoo and one single agent example (#782) (@Mytolo) - Update mpo.jl (#783) (@HenriDeh) - Reduce unnecessary array allocations (#785) (@jeremiahpslewis) - Temporarily disable failing experiment so project tests pass (#787) (@jeremiahpslewis) - Fix spellcheck errors (#788) (@jeremiahpslewis) - Bug fixes and dependency bump (#789) (@jeremiahpslewis) - Reactivate some tests for RLExperiments (#790) (@jeremiahpslewis) - Pin ReinforcementLearning.jl to pre-refactor versions (#793) (@jeremiahpslewis) - Update TagBot.yml (#794) (@jeremiahpslewis) - Drop RL.jl as dependency from Experiments (#795) (@jeremiahpslewis) - Fix compat for RLBase (#796) (@jeremiahpslewis) - Fix RLCore version, prep for bump (#797) (@jeremiahpslewis) - Add reexport compat (#798) (@jeremiahpslewis) - Bump compat helper (#799) (@jeremiahpslewis) - Fix IntervalSets compat for RLEnvironments (#800) (@jeremiahpslewis) - Bump RLZoo.jl version for release (#815) (@jeremiahpslewis) - Fix RLExperiments compat (#816) (@jeremiahpslewis) - Expand RLZoo compat (#817) (@jeremiahpslewis) - Bump RLExperiments, require 0.11 (#818) (@jeremiahpslewis) - Pin ReinforcementLearningZoo.jl to 0.6 in RLExperiments (#819) (@jeremiahpslewis) - Drop RL.jl from CompatHelper (until refactor complete) (#824) (@jeremiahpslewis) - Bump Github Actions cache version (#825) (@jeremiahpslewis) - Basic allocation fixes for RandomWalk / RandomPolicy (#827) (@jeremiahpslewis) - Bump CI.yml GitHub action versions (#828) (@jeremiahpslewis) - Add tests, improve performance of RewardsPerEpisode (#829) (@jeremiahpslewis) - Refactor and add tests to TotalBatchRewardPerEpisode (#830) (@jeremiahpslewis) - Tests, refactor for TimePerStep (#831) (@jeremiahpslewis) - DoEveryNStep tests, performance tweaks (#832) (@jeremiahpslewis) - Add DoOnExit test (#833) (@jeremiahpslewis) - Expand PR Template (#835) (@jeremiahpslewis) - Fix branch name (master -> main) (#837) (@jeremiahpslewis) - Add test_noop! to remaining hooks (#840) (@jeremiahpslewis) - Make TimePerStep test robust (#841) (@jeremiahpslewis) - Reactivate docs (#842) (@jeremiahpslewis) - Add activate_devmode!() explanation to tips.md (#845) (@jeremiahpslewis) - Bump compat of RL.jl to 0.11.0-dev (#846) (@jeremiahpslewis) - add kwargs to agent (#847) (@HenriDeh) - Gaussian network refactor and tests (#849) (@HenriDeh) - Agent Refactor (#850) (@jeremiahpslewis) - Bump RLCore (#851) (@jeremiahpslewis) - Include codecov in CI (#854) (@HenriDeh) - Fix a typo in MPO (#855) (@HenriDeh) - DoEvery should not trigger on t = 1 (#856) (@HenriDeh) - update CI Julia version (#857) (@jeremiahpslewis) - Tweak CI to check on dep changes (#858) (@HenriDeh) - CompatHelper: bump compat for FillArrays to 1 for package ReinforcementLearningCore, (keep existing compat) (#859) (@github-actions[bot]) - MultiAgent Proposal (#861) (@jeremiahpslewis) - CompatHelper: add new compat entry for ReinforcementLearningCore at version 0.9 for package ReinforcementLearningEnvironments, (keep existing compat) (#865) (@github-actions[bot]) - Multiplayer Fixes (Clean up errors) (#867) (@jeremiahpslewis) - Added a section to the home page about getting help for Reinforcement… (#868) (@LooseTerrifyingSpaceMonkey) - Bump StatsBase compat (#873) (@jeremiahpslewis) - ComposedHooks, MultiHook fixes (#874) (@jeremiahpslewis) - Fix RLEnvs compat (#875) (@jeremiahpslewis) - Add back ComposedStop (#876) (@jeremiahpslewis) - Bump RLBase to v0.11.1 (#877) (@jeremiahpslewis) - Further refinements (#879) (@jeremiahpslewis) - Use multiple dispatch / methods plan! and act! (#880) (@jeremiahpslewis) - RLCore.update! -> Base.push! API change (#884) (@jeremiahpslewis) - Add compat for CommonRLInterface (#886) (@jeremiahpslewis) - Fix hook issues (#887) (@jeremiahpslewis) - CompatHelper: bump compat for ReinforcementLearningZoo to 0.6 for package ReinforcementLearningExperiments, (keep existing compat) (#888) (@github-actions[bot]) - Stacknamespace (#889) (@HenriDeh) - allow more recent versions (#890) (@HenriDeh) - Fix stack (#891) (@HenriDeh) - CompatHelper: add new compat entry for DelimitedFiles at version 1 for package ReinforcementLearningEnvironments, (keep existing compat) (#894) (@github-actions[bot]) - Update implement new alg docs (#896) (@jeremiahpslewis) - NFQ (#897) (@CasBex) - fixed problem with sequential multi agent envs (#898) (@Mytolo) - Sketch out optimise! refactor (#899) (@jeremiahpslewis) - Bug fix optimise! (#902) (@jeremiahpslewis) - Breaking changes to optimise! interface: Bump RLCore to v0.11 and RLZoo to v0.8 (#903) (@jeremiahpslewis) - Swap out rng code (#905) (@jeremiahpslewis) - CompatHelper: bump compat for NNlib to 0.9 for package ReinforcementLearningZoo, (keep existing compat) (#906) (@github-actions[bot]) - Fix dispatch and update documentation (#907) (@HenriDeh) - QBasedPolicy optimise! forwards to learner. (#909) (@HenriDeh) - Bump RLZoo version for NNlib (#911) (@jeremiahpslewis) - Add performance testing run loop (#914) (@jeremiahpslewis) - Fix Timer bug (#915) (@jeremiahpslewis) - couple of improvements to MPO (#919) (@HenriDeh) - Rework the run loop (#921) (@HenriDeh) - adjusted pettingzoo to PettingZooEnv simultaneous environment more co… (#925) (@Mytolo) - fixed devmode / project files (#932) (@Mytolo) - fixed DQNLearner Gpu isse (#933) (@Mytolo) - fixing prob. /w symbol/ string correspondence (#934) (@Mytolo) - Bump flux compat (#935) (@jeremiahpslewis) - Reduce find_all_max allocations and increase speed based on chatgpt s… (#938) (@jeremiahpslewis) - Add Buildkite / GPU tests (#942) (@jeremiahpslewis) - Add RLZoo and RLExperiments to Buildkite (#943) (@jeremiahpslewis) - Drop deprecated @provide interface (#944) (@jeremiahpslewis) - CI Improvements (#946) (@jeremiahpslewis) - Github Actions Fixes (#947) (@jeremiahpslewis) - gpu updates RLExperiments, RLZoo (#949) (@jeremiahpslewis) - Bump RLCore version (#950) (@jeremiahpslewis) - Refactor TRPO and VPG with EpisodesSampler (#952) (@HenriDeh) - Fix TotalRewardPerEpisode bug (#953) (@jeremiahpslewis) - update docs to loop refactor (#955) (@HenriDeh) - CompatHelper: bump compat for ReinforcementLearningCore to 0.13 for package ReinforcementLearningEnvironments, (keep existing compat) (#956) (@github-actions[bot]) - CompatHelper: bump compat for ReinforcementLearningCore to 0.13 for package ReinforcementLearningZoo, (keep existing compat) (#957) (@github-actions[bot]) - CompatHelper: bump compat for ReinforcementLearningCore to 0.13 for package ReinforcementLearningExperiments, (keep existing compat) (#958) (@github-actions[bot]) - CompatHelper: add new compat entry for cuDNN at version 1 for package ReinforcementLearningCore, (keep existing compat) (#962) (@github-actions[bot]) - CompatHelper: add new compat entry for cuDNN at version 1 for package ReinforcementLearningZoo, (keep existing compat) (#963) (@github-actions[bot]) - CompatHelper: add new compat entry for cuDNN at version 1 for package ReinforcementLearningExperiments, (keep existing compat) (#964) (@github-actions[bot]) - TargetNetwork (#966) (@HenriDeh) - CompatHelper: bump compat for GPUArrays to 9 for package ReinforcementLearningCore, (keep existing compat) (#969) (@github-actions[bot]) - Prioritised DQN GPU (#974) (@CasBex) - CompatHelper: bump compat for ReinforcementLearningCore to 0.13 for package ReinforcementLearningZoo, (keep existing compat) (#975) (@github-actions[bot]) - CompatHelper: bump compat for ReinforcementLearningZoo to 0.8 for package ReinforcementLearningExperiments, (keep existing compat) (#976) (@github-actions[bot]) - CompatHelper: bump compat for ReinforcementLearningCore to 0.13 for package ReinforcementLearningExperiments, (keep existing compat) (#977) (@github-actions[bot]) - Nfq refactor (#980) (@CasBex) - Fix and refactor SAC (#985) (@HenriDeh) - CompatHelper: bump compat for DomainSets to 0.7 for package ReinforcementLearningBase, (keep existing compat) (#986) (@github-actions[bot]) - remove rlenv dep for tests (#989) (@HenriDeh) - CompatHelper: add new compat entry for CUDA at version 5 for package ReinforcementLearningExperiments, (keep existing compat) (#991) (@github-actions[bot]) - CompatHelper: add new compat entry for IntervalSets at version 0.7 for package ReinforcementLearningExperiments, (keep existing compat) (#994) (@github-actions[bot]) - Conservative Q-Learning (#995) (@HenriDeh) - CompatHelper: add new compat entry for Parsers at version 2 for package ReinforcementLearningCore, (keep existing compat) (#997) (@github-actions[bot]) - CompatHelper: add new compat entry for MLUtils at version 0.4 for package ReinforcementLearningZoo, (keep existing compat) (#998) (@github-actions[bot]) - CompatHelper: add new compat entry for Statistics at version 1 for package ReinforcementLearningCore, (keep existing compat) (#999) (@github-actions[bot]) - Update CQL_SAC.jl (#1003) (@HenriDeh) - Bump tj-actions/changed-files from 35 to 41 in /.github/workflows (#1006) (@dependabot[bot]) - Make it compatible with Adapt 4 and Metal 1 (#1008) (@joelreymont) - Bump RLCore, RLEnv (#1012) (@jeremiahpslewis) - Fix PPO per [#1007] (#1013) (@jeremiahpslewis) - Fix RLCore version (#1018) (@jeremiahpslewis) - Add Devcontainer, handle DomainSets 0.7 (#1019) (@jeremiahpslewis) - Initial GPUArray transition (#1020) (@jeremiahpslewis) - Update TagBot.yml for subprojects (#1021) (@jeremiahpslewis) - Fix offline agent test (#1025) (@joelreymont) - Fix spell check CI errors (#1027) (@joelreymont) - GPU Code Migration Part 2.1 (#1029) (@jeremiahpslewis) - Bump RLZoo to v0.8 (#1031) (@jeremiahpslewis) - Fix RLZoo version (#1032) (@jeremiahpslewis) - Drop devmode, prepare RL.jl v0.11 for release (#1035) (@jeremiahpslewis) - Update docs script for new 'limited' RL.jl release (#1038) (@jeremiahpslewis) - Tabular Approximator fixes (pre v0.11 changes) (#1040) (@jeremiahpslewis) - Swap RLZoo for RLFarm in CI, drop RLExperiments (#1041) (@jeremiahpslewis) - Buildkite tweaks for monorepo (#1042) (@jeremiahpslewis) - Drop archived projects (#1043) (@jeremiahpslewis) - Simplify Experiment code after dropping RLExperiment (#1044) (@jeremiahpslewis) - Fix code coverage scope so it ignores test dir (#1045) (@jeremiahpslewis) - Fix reset and stop conditions (#1046) (@jeremiahpslewis) - Drop Functors and use Flux.@layer (#1048) (@jeremiahpslewis) - Fix naming consistency and add missing hook tests (#1049) (@jeremiahpslewis) - Add SARS tdlearning back to lib (#1050) (@jeremiahpslewis) - Update FluxModelApproximator references to FluxApproximator (#1051) (@jeremiahpslewis) - Epsilon Speedy Explorer (#1052) (@jeremiahpslewis) - Add TotalRewardPerEpisodeLastN hook (#1053) (@jeremiahpslewis) - Fix abstract_learner for multiplayer games (#1054) (@jeremiahpslewis) - Update versions (#1055) (@jeremiahpslewis) - Update Docs for v0.11 release (#1056) (@jeremiahpslewis) - Update Katex version, fix vulnerability (#1058) (@jeremiahpslewis) - Add missing Flux compat (#1059) (@jeremiahpslewis) - Fix docs / website build (#1064) (@jeremiahpslewis) - Correct Pendulum x-y coordinates (#1065) (@HenriDeh) - Make QBasedPolicy general for AbstractLearner s (#1069) (@dharux) - Fix hooks for multiplayer case (#1071) (@jeremiahpslewis) - Fix doc build errors (#1072) (@jeremiahpslewis) - bump rlcore version (#1073) (@jeremiahpslewis) - Make FluxApproximator work with QBasedPolicy (#1075) (@jeremiahpslewis) - Fix RLEnvs version (#1076) (@jeremiahpslewis) - Fix TagBot (#1077) (@jeremiahpslewis) - Fix docs homepage (#1082) (@michalrzak) - Jpsl/update flux (#1086) (@jeremiahpslewis) - Bump RLFarm compat (#1087) (@jeremiahpslewis)

Closed issues: - A3C (#133) - Box2D environment (#2) - Visualize episodes (#3) - Implement TRPO/ACER (#134) - ERROR: UndefVarError: AtariPreprocessor not defined (#6) - bullet3 environment (#7) - vizdoom environment (#8) - Error tagging new release (#11) - loadenvironment error (#19) - Support alternative deep learning libraries (#20) - Random Thoughts on v0.3.0 (#24) - ViZDoom is broken (#130) - Document basic environments (#129) - bullet3 environment (#128) - Box2D environment (#127) - Prioritized DQN (#27) - Improve interfaces for model exploration and hyperparameter optimization (#28) - A2C (#32) - Add built-in support for TensorBoard (#35) - Add checkpoints (#36) - Improve code coverage (#40) - AbstractActionSelector not exported (#41) - Params empty - no tracking (#43) - Add reproducible examples for Atari environments (#44) - Add procgen (#126) - StopAfterEpisode with progress meter (#51) - Add MAgent (#125) - Regret Policy Gradients (#131) - Support SEED RL (SCALABLE AND EFFICIENT DEEP-RL ) (#62) - Support julia 1.4 (#63) - How to define a new environment? (#64) - Roadmap of v0.9 (#65) - Add MCTS related algorithms (#132) - Question about AbstractEnv API (#68) - bsuite (#124) - Classic environments in separate package? (#123) - Implement Fully Parameterized Quantile Function for Distributional Reinforcement Learning. (#135) - Failed to precompile ReinforcementLearning (#71) - Experimental support of Torch.jl (#136) - depends on HDF5? (#72) - warning and error (#73) - Compatibility issue in ReinforcementLearning & Flux (#74) - ERROR: KeyError: key "ArnoldiMethod" not found (#79) - Add dueling DQN (#137) - In DDPG: Add support for vector actions (#138) - Rename AbstractAgent to AbstractPolicy (#111) - How should ReinforcementLearning.jl be cited ? (#80) - Add a stop condition to terminate the experiment after reaching reward threashold (#112) - Add Game 2048 (#122) - add CUDA accelerated Env (#121) - Unify common network architectures and patterns (#139) - Alternative handling of max steps in environment (#140) - I get NNlib error when trying to load a model (#82) - "convert" warning (#83) - Seg fault on macbook pro (#84) - ACME RL lib by deepmind (#85) - Add Highway env (#120) - Definition of a policy (#86) - Add remote trajectories (#87) - Add experiments based on offline RL data (#141) - Asynchronous Methods for Deep Reinforcement Learning (#142) - Base.convert method for DiscreteSpace (#104) - Action Space Meaning (#88) - Base.in method for EmptySpace (#105) - Renaming get_terminal to isterminated (#106) - Requesting more informative field names for SharedTrajectory (#113) - R2D2 (#143) - Suggestion: More informative name for FullActionSet & MinimalActionSet (#107) - Returning an AbstractSpace object using get_actions (#108) - Recurrent Models (#144) - Split experiments into separate files (#145) - Add project.toml for tests (#146) - Migrate to Pluto (#148) - Update dependency to the latest version of ReinforcementLearning.jl (#149) - Docs build error (#91) - Split out Trajectory & CircularArrayBuffer as independent packages (#114) - Requesting explanation for better performance at ... (#115) - Add an extra mode when evaluating agent (#116) - Why are wrapper environments a part of RLBase instead of RLCore (say)? (#109) - Purpose and scope of sub-packages (#93) - The names of keyword arguments in Trajectory is kind of misunderstanding (#117) - Add experiments with GymEnv (#147) - Cross language support (#103) - Check compatibility between agent and environments (#118) - Behaviour for hooks for RewardOverridenEnv (#119) - StopAfterEpisode with custom DQNL errors beyond a particular Episode Count (#96) - ERROR: UndefVarError: NNlib not defined while loading agent (#110) - Support compression? (#102) - State monitoring and fault tolerance (#101) - Use JLSO for (de)serialization? (#97) - Add an example running in K8S (#100) - Setup github actions (#98) - Fails to load trajectory (#150) - Replace Travis with github actions (#151) - Test error in ReinforcementLearningEnvironments.jl (#152) - Move preallocations in MultiThreadEnv from global to local (#153) - Flux as service (#154) - remove @views (#155) - error in save & load ElasticCompactSARTSATrajectory (#156) - add early stopping in src\core\stop_conditions.jl (#157) - add time stamp in load & save function, in file src\components\agents\agent.jl (#158) - policies in GPU can not be saved || loaded (#159) - AbstractStage docstring doesn't render correctly in docs. (#160) - List of contributors (#161) - code formatting (#165) - Purpose of CommonRLInterface (#166) - Moving example environments from RLBase to RLEnvs? (#167) - Keeping prefix get_ in method names like get_reward (#168) - Currently getting an ambiguous method error in ReinforcementLearningCore v0.5.1 (#171) - Return experiment instead of hook only (#173) - TD3 Implementation (#174) - Train policy with GymEnv (#175) - Travis CI Credits (#178) - Training mode and testing mode (#179) - Unrecognized symbols (#180) - AbstractEnv (#181) - SARTTrajectory for SAC (#182) - define environment of FULL_ACTION_SET (#184) - CircularArraySLARTTrajectory instance is not of type CircularArraySLARTTrajectory (#185) - TagBot trigger issue (#186) - Is hook the same thing as "callback"? (#190) - Use @threads instead of @sync + @spawn in MultiThreadEnv? (#191) - Blog custom env link typo (#192) - Change clip_by_global_norm! into a Optimizer (#193) - PPO related algorithms are broken (#194) - Add card game environments (#196) - Separate envs from algos in Zoo? (#197) - Why "examples"? (#198) - WandB integration? (#201) - Add default implementations for AbstractEnvWrapper (#202) - Add configuration in DQNLearner to enable double-dqn by default (#205) - Derivative-Free Reinforcement Learning (#206) - ERROR: type RandomPolicy has no field policy (#208) - Why split repos? (#209) - "Getting Started" too long imo (#210) - PreActStage clarification (#212) - What's a "trace"? (#213) - Continuous time supported? (#215) - Docs looks ugly in dark mode (#217) - Julia 1.6.0 dependency problem with ReinforcementLearningBase/RLBase (#221) - Add Discrete Batch-Constrained Deep Q-learning (#226) - Docstring of DoEveryNStep (#225) - Documentation of environment; actions seems not work. (#222) - Documentation of "How to use Tensorboard?": with_logger not defined (#223) - Getting figure object; How to get an animation using GR.plot in CartPolEnv (#246) - Update dependency to Julia@v1.6 and resolve type piracy of findmax (#227) - IQN is broken with Julia@v1.6 (#228) - The components of Rainbow (#229) - Source links in documentation directs to julia repo (#231) - Support Tables.jl and PrettyTables.jl for Trajectories (#232) - code in get_started seems to be broken (#233) - PPO strange behaviour from having actions as one element arrays instead of scalar (#234) - SAC and GaussianNetwork (#236) - Precompilation prohibitively long (#237) - Document how to save/load parameters (#238) - Workflow of saving trajectory data (#239) - An explanation of "how to train policy (agent)" such as Basic_DQN would be valuable (#240) - How to guarantee the environment's reproducibility? (#241) - [Call for Contributors] Summer 2021 of Open Source Promotion Plan (#242) - Cannot use RLBase.action_space etc. when writing my own environment (#244) - ReinforcementLearningZoo.jl experiments (#245) - Next Release Plan (v0.9) (#247) - How about making this package compatible with DifferentialEquations.jl? (#249) - Reinforcement Learning and Combinatorial Optimization (#250) - PPO and multi dimensional actions spaces (#251) - Add ReinforcementLearningDatasets (#253) - Incompatibility with CSVFiles.jl (#256) - [RLEnvs] easy access of the length of an action vector (dimension of action space) (#257) - Cannot add LinearAlgebra (#258) - What's the checkpoints? (#261) - Model based reinforcement learning (#262) - Add a dedicated multi-dimensional space type (#268) - PPO is broken when using CUDA (#280) - Lack of reproducibility of QRDQN CartPole Experiment. (#281) - Reinforcement Learning.jl in a RTS (#291) - StopAfterNoImprovement hook test fails occasionally (#297) - Get error when using ReinforcementLearning (#298) - Problems with PGFPlotsX during the install (#301) - Plotting CartPole environment in Jupyter (#306) - Support CircularVectorSARTTrajectory RLZoo (#316) - Local development environment setup tips causing error (#320) - Rename some functions to help beginners navigate source code (#326) - Question about PER (#328) - Docs error in code output (#332) - Setup a CI for typo (#336) - double code & dysfunctional master branch when downloading package (#341) - Support multiple discrete action space (#347) - Precompilation error; using Plots makes a conflict (#349) - Problem with running initial tutorial. Using TabularPolicy() generates an UndefinedKeyword error for n_action (#354) - Question: Clarification on the RL plots generated by the run() function (#357) - prob question for QBasedPolicy (#360) - Can evaluate function be used as a component of RLcore? (#369) - problem about precompiling the forked package (#377) - Question: Can we use packages like DifferentialEquations.jl to evolve or model the environment in ReinforcementLearning.jl (#378) - Combine transformers and RL (#392) - MultiAgentManager does not select correct action space for RockPaperScissorsEnv (#393) - Add ReinforcementLearningDatasets.jl (#397) - error: dimension mismatch "cannot broadcast array to have fewer dimensions" (#400) - SAC policy problems? (#410) - Add pre-training hook (#411) - Dead links in documentation (#418) - Links of show nbview badges in RLExperiments are incorrect (#421) - Problem accessing public google cloud storage bucket for RLDatasets.jl (#424) - Function to access base env through multiple wrapper layers (#425) - The problem of using GaussianNetwork in gpu (#455) - Next Release Plan (v0.10) (#460) - Error in experiment "JuliaRL_DDPG_Pendulum" (#471) - In Windows, ReinforcementLearningDataset.jl encounter a bug (#485) - Conditional Testing (#493) - Inconsistency of the EpsilonGreedyExplorer selection function (#520) - PyCall.getindex in module ReinforcementLearningEnvironments conflict warning (#527) - device method definition overwritten (#530) - How to display/render AtariEnv? (#546) - StackFrames bug? (#551) - Refactor of DQN Algorithms (#557) - Small performance improvement (#558) - Infinite-recursion bug in function is_discrete_space when an object of type ClosedInterval is passed (#566) - JuliaRL_BasicDQN_CartPole example fails (#568) - action_space not defined in tutorial (#569) - CI fails with Julia@v1.7 (#572) - Warning while precompiling RLCore due to kwargs (#575) - Gain in VPGPolicy does not account for terminal states? (#578) - Strange Bug with examples CartPoleEnv and RLBase.test_runnable!(RandomWalk1D) (#579) - Missing docs for TDLearner (#580) - Difficulty Creating a Custom Environment (#581) - Missing docs for how to implement a new algorithm (#582) - Donation (#595) - MultiThreadEnv with custom (continuous) action spaces fails (#596) - PPOCartPole fails, source of error included (#605) - Question: Can ReinforcementLearning.jl handle Partially Observed Markov Processes (POMDPs)? (#608) - Next Release Plan (v0.11) (#614) - Add an environment wrapper to IsaacGym (#619) - Explain current implementation of PPO in detail (#620) - How to run this source code in vscode? (#623) - Bug: Issue with TD3 for multi-dimensional action spaces (#624) - Make documentation on trace normalization (#633) - ActionTransformedEnv doesn't transform legal_action_space_mask (#642) - Bug: Previous example from RLZoo now has a bug (#643) - TDLearner time step parameter (#648) - Examples of multidimensional continous actions (#676) - estimate v.s. basis in policies (#677) - Base.copy not implemented for the TicTacToe environment (#678) - Broken link to src (#693) - Support Brax (#696) - Q-learning update timing (#702) - PPO on environments with multiple action dimensions? (#703) - Can't checkout RLCore for development (#704) - various eligibility trace-equipped TD methods (#709) - Improve the logging mechanism during training (#725) - questions while looking at implementation of VPG (#729) - Setup sponsor related info (#730) - new _run() (#731) - SAC example experiment does not work (#736) - Custom environment action and state space explanation (#738) - PPOPolicy training: ERROR: DomainError with NaN: Normal: the condition σ >= zero(σ) is not satisfied. (#739) - Code Readability (#740) - MultiThreadEnv not available in ReinforcementLearningZoo (#741) - ReinforcementLearningExperiment dependencies fail to precompile (#744) - tanh normalization destabilizes learning with GaussianNetwork (#745) - how to load a saved model and test it? (#755) - Custom Environment Passes RLBase.test_runnable!(env) but infinite hangs and crashes when run. (#757) - Bounds Error at UPDATE_FREQ Step (#758) - StopAfterEpisode returns 1 more episode using StepsPerEpisode() hook (#759) - Move basic definition of environment wrapper into RLBase (#760) - Precompilation error - DomainSets not in dependencies (#761) - How to set RLBase.state_space() if the number of state space is uncertain (#762) - Collect both number of steps and rewards in a single hook (#763) - how to use MultiAgentManager on different algorithms? (#764) - Example run of Offline RL that totally depends on dataset without online environment (#765) - Every single environment / experiment crashes with following error: (#766) - Neural Network Approximator based policies not working (#770) - Deep RL example for LSTM (#772) - "params not defined," "JuliaRL_BasicDQN_CartPole" (#778) - MonteCarloLearner incorrect PreActStage behavior (#779) - Prioritised Experience Replay (#780) - Outdated dependencies (#781) - Running experiments throws a "UndefVarError: params not defined" message (#784) - Failing MPOCovariance experiment (#791) - Package Stabilization Plan (#792) - Logo image was not found (#836) - Reactivate docs on CI/CD (#838) - test/runtests.jl empty (+ arch discussion) (#843) - update docs: Tips for developers (#844) - policy(env) returns no legal action -inf initialized Q-table (#852) - Package dependencies not compatible (#860) - need help from an expert (#862) - Installing ReinforcementLearning.jl downgrades Flux.jl (#864) - Refactor CI into separate Workflows per package (and separate codecov projects per package) (#869) - Fix Experiment type setup (#881) - LoadError: UndefVarError: params not defined (#882) - Rename update! to push! (#883) - Add deprecation warnings to non-refactored policies (#892) - Contribute Neural Fitted Q-iteration algorithm (#895) - Vectorized environments (#908) - PPo policy experiments failing (#910) - Loading a Gym Environment (#912) - Executing RLBase.plan! after end of experiment (#913) - PPO with MaskedPPOTrajectory (#917) - Devmode is not working (#918) - EpisodeSampler in Trajectories (#927) - Hook RewardsPerEpisode broken (#945) - TD3 Policy unable to handle environments with multidimensional action spaces (#951) - Spin off core packages (#960) - Can implement this ARZ algorithm ? (#965) - AssertionError: action in env.action_space (#967) - Fixing SAC Policy (#970) - Prioritized DQN experiment nonfunctional (#971) - Prioritised DQN failing on GPU (#973) - experiments failed (#982) - An error (#983) - params() is no longer supported in Flux (#996) - Breaking the tutorial by getting TotalRewardPerEpisode out of sync with the stopping condition in a run call (#1000) - GPU Compile error on PPO with MaskedPPOTrajectory (#1007) - RL Core tests fail sporadically (#1010) - RL Env tests fail with latest OpenSpiel patches (#1011) - Tutorial OpenSpiel KuhnOpenNSFP fails (#1024) - CI: Should spell check be dropped or fixed? (#1026) - Transfer Algorithms to RLFarm (#1028) - Update Buildkite script for gpu testing so it's sub package compatible (#1030) - Simple ReinforcementLearning example crashes (#1034) - Website: A practical introduction to RL: Does not introduce, source code is broken (#1036) - Website: How do implement a new algorithm is outdated (#1037) - Review TabularApproximator (#1039) - ElasticArraySARTSTraces does not record the trajectories of MountainCarEnv() correctly (#1067) - Algorithm implementations (#1070) - No method matching iterate ArrayProductDomain (#1074)