├── .gitignore ├── LICENSE ├── README.md ├── marl-book-ch1-ch2-intro-rl.pdf ├── marl-book-ch3-games.pdf ├── marl-book-ch4-solution-concepts.pdf ├── marl-book-ch5-marl-in-games.pdf ├── marl-book-ch6-marl-algorithms.pdf ├── marl-book-ch7-deep-learning.pdf ├── marl-book-ch8-deep-rl.pdf ├── marl-book-ch9-part1-deep-marl.pdf ├── marl-book-ch9-part2-deep-marl.pdf └── source ├── images ├── 1.1_multi_agent_system.png ├── 1_LBF.png ├── 1_MARL_book.png ├── 1_RL_definition.png ├── 1_SARL_diagram.png ├── 1_learning_curves.png ├── 1_marl_schematic.png ├── 1_mars_rover_mdp.png ├── 1_mdp_diagram.pdf ├── 1_mdp_diagram.tex ├── 1_mdp_diagram_elipses.pdf ├── 1_policy_iteration.png ├── 1_reware.png ├── 1_self_driving.png ├── 1_starcraft.png ├── 1_trading.png ├── 1_warehouse.png ├── 2_stochastic_game_diagram.tex ├── MARL-loop-JAL-a.pdf ├── MARL-loop-JAL-b.pdf ├── MARL-loop-JAL-c.pdf ├── SG-value-iter.pdf ├── agent_modelling_encoder_decoder_targets.drawio ├── agent_modelling_encoder_decoder_targets.pdf ├── alphastar_starcraft.jpg ├── chapter6 │ ├── agentmodel.pdf │ ├── dirichlet.pdf │ ├── dirichlet.png │ ├── fp_empirical_distribution_cg.pdf │ ├── fp_empirical_distribution_cg_aa.pdf │ ├── fp_empirical_distribution_cg_bb.pdf │ ├── fp_empirical_distribution_pd.pdf │ ├── fp_empirical_distribution_rps.pdf │ ├── fp_rps_table.pdf │ ├── iga_imaginary.pdf │ ├── iga_noninvert.pdf │ ├── iga_real.pdf │ ├── iga_wolf.pdf │ ├── nosde.pdf │ ├── regmat_rps_empdist1.pdf │ ├── regmat_rps_empdist2.pdf │ ├── regmat_rps_empdist3.pdf │ ├── regmat_rps_policy1.pdf │ ├── regmat_rps_policy2.pdf │ ├── regmat_rps_policy3.pdf │ ├── regmat_rps_regret1.pdf │ ├── regmat_rps_regret2.pdf │ ├── regmat_rps_regrets.pdf │ ├── simple-soccer.pdf │ ├── tabular_marl_lbf.pdf │ ├── tabular_marl_lbf_eplength_all.pdf │ ├── tabular_marl_lbf_returns_all.pdf │ ├── vi-example-coop.pdf │ ├── vi-example-grim.pdf │ ├── vi-pd-example.pdf │ └── wolfphc_rps_own.pdf ├── chapter_1 │ ├── MARL-loop.pdf │ ├── mas_schematic.pdf │ └── mas_schematic_old.pdf ├── chapter_2 │ ├── RL-loop.pdf │ ├── mdp-rover.pdf │ ├── rl-learning-problem.pdf │ ├── tabular_mdp_eplength.pdf │ ├── tabular_mdp_ql_alphas_eplength.pdf │ ├── tabular_mdp_ql_alphas_returns.pdf │ ├── tabular_mdp_ql_eps_decay.pdf │ ├── tabular_mdp_ql_eps_eplength.pdf │ ├── tabular_mdp_ql_eps_returns.pdf │ └── tabular_mdp_returns.pdf ├── chapter_3 │ ├── POSG_hierarchy.pdf │ ├── communication example.pdf │ ├── communication_example.pdf │ ├── game-hierarchy.pdf │ ├── game-models-mg.pdf │ ├── game-models-posg.pdf │ ├── game-models-sg.pdf │ ├── normal_form_hierarchy.pdf │ └── stochastic_games_hierarchy.pdf ├── chapter_4 │ ├── PPAD.pdf │ ├── battlesexes-po-frontier.pdf │ ├── chicken-po-frontier.pdf │ ├── marl-learning-problem.pdf │ ├── nf_inputs-1.pdf │ ├── posg_input-1.pdf │ ├── rnf_input-1.pdf │ └── sg_input-1.pdf ├── chapter_5 │ ├── learning-process.pdf │ ├── tabular_marl_lbf_eplength_iql_cql.pdf │ ├── tabular_marl_lbf_returns_iql_cql.pdf │ └── wolfphc_rps_own.pdf ├── chapter_7 │ ├── activation_functions.pdf │ ├── cnn.pdf │ ├── dl_training_loop.pdf │ ├── feedforward_neural_network.pdf │ ├── gradient_optimisation_contour.pdf │ ├── gradient_optimisation_f.pdf │ ├── gradient_optimisation_loss.pdf │ ├── gradient_optimisation_loss_3d.pdf │ ├── gradient_optimisation_momentum_contour.pdf │ ├── gradient_optimisation_momentum_loss.pdf │ ├── maze.pdf │ ├── neural_unit.pdf │ ├── rnn.pdf │ └── sgd.pdf ├── chapter_8 │ ├── a2c_lbf_nstep_comparison.pdf │ ├── a2c_nstep_variance_bias_Foraging-8x8-1p-1f-v2_100000.pdf │ ├── a2c_parallel_envs_speed.pdf │ ├── a2c_parallel_envs_steps.pdf │ ├── a2c_parallel_envs_time.pdf │ ├── asynchronous_training.pdf │ ├── dqn_architecture.pdf │ ├── epsilon_greedy_policies.pdf │ ├── lunarlander.pdf │ ├── lunarlander_left1.pdf │ ├── lunarlander_right1.pdf │ ├── lunarlander_right2.pdf │ ├── pg_lbf_returns.pdf │ ├── pg_lbf_returns_gamma1.pdf │ ├── single_agent_lbf.pdf │ ├── single_agent_lbf_nolevel.pdf │ ├── softmax_policy.pdf │ ├── synchronous_training.pdf │ ├── vb_lbf_returns.pdf │ └── vb_lbf_returns_gamma1.pdf ├── chapter_9 │ ├── ac_am-foraging_8x8_2p_2f_coop.pdf │ ├── agent_modelling_encoder_decoder.pdf │ ├── bps_game_parametersharing.pdf │ ├── bps_spread.pdf │ ├── centralv-speaker-listener.pdf │ ├── chess-board-transform.png │ ├── chess-board.png │ ├── coordination-graph.pdf │ ├── ia2c-on-lbf-2p.pdf │ ├── ia2c-on-lbf-3p.pdf │ ├── jal_am-foraging_5x5_2p_2f_coop.pdf │ ├── jal_am-foraging_5x5_3p_3f.pdf │ ├── macac_architecture.pdf │ ├── matrixgame-twostep-qmix.pdf │ ├── matrixgame-twostep-vdn.pdf │ ├── matrixgame-twostep.pdf │ ├── mcts-backprop.pdf │ ├── mcts-expand.pdf │ ├── pac-climbing.pdf │ ├── pac-lbf.pdf │ ├── parameter-sharing.pdf │ ├── psro-game.pdf │ ├── psro-oracle.pdf │ ├── psro-solve.pdf │ ├── psro.pdf │ ├── qmix_architecture.pdf │ ├── qmix_mixing.pdf │ ├── qmix_mixing3d.pdf │ ├── qmix_mixing3d_bw.pdf │ ├── qmix_mixing_bw.pdf │ ├── speaker-listener.pdf │ ├── v_architecture.pdf │ ├── vd_lbf-8x8-2p-2f-coop.pdf │ ├── vd_lbf-8x8-2p-3f.pdf │ ├── vdn_architecture.pdf │ ├── vdn_mixing.pdf │ ├── vdn_mixing3d.pdf │ └── vdn_mixing_bw.pdf ├── environments │ └── lbf │ │ ├── 8x8-3p-5f-coop.png │ │ ├── 8x8-3p-5f.png │ │ ├── foraging_8x12_a.png │ │ ├── foraging_8x12_b.png │ │ ├── foraging_po.png │ │ ├── lbf-5x5-2p-2f-coop.png │ │ ├── lbf-8x8-2p-2f-coop.png │ │ ├── lbf-8x8-2p-3f.png │ │ ├── lbf_po.pdf │ │ ├── tabular_marl_lbf.pdf │ │ └── tabular_marl_lbf_annot.pdf ├── game-tree.drawio ├── game-tree.pdf ├── go_board.jpg ├── lbf_6x6-2p-1f.jpg ├── marl-book-cover.jpg ├── marl-book-cover.pdf ├── marl_paradigms.drawio ├── marl_paradigms.pdf ├── marl_paradigms_no_ctde.drawio ├── marl_paradigms_no_ctde.pdf ├── minimax_soccer.pdf ├── minimax_soccer_results_a.pdf ├── minimax_soccer_results_a.png ├── minimax_soccer_results_b.pdf ├── minimax_soccer_results_b.png ├── minimax_soccer_results_c.pdf ├── minimax_soccer_results_c.png ├── nature_alphago.jpg ├── parameter_sharing.drawio ├── parameter_sharing.pdf ├── parameter_sharing_cut.drawio ├── parameter_sharing_cut.pdf ├── parameter_sharing_mix.drawio ├── parameter_sharing_mix.pdf ├── parameter_sharing_simple.drawio └── parameter_sharing_simple.pdf ├── make.sh ├── marl-book-ch1-ch2-intro-rl.pdf ├── marl-book-ch1-ch2-intro-rl.tex ├── marl-book-ch3-games.pdf ├── marl-book-ch3-games.tex ├── marl-book-ch4-solution-concepts.pdf ├── marl-book-ch4-solution-concepts.tex ├── marl-book-ch5-marl-in-games.pdf ├── marl-book-ch5-marl-in-games.tex ├── marl-book-ch6-marl-algorithms.pdf ├── marl-book-ch6-marl-algorithms.tex ├── marl-book-ch7-deep-learning.pdf ├── marl-book-ch7-deep-learning.tex ├── marl-book-ch8-deep-rl.pdf ├── marl-book-ch8-deep-rl.tex ├── marl-book-ch9-part1-deep-marl.pdf ├── marl-book-ch9-part1-deep-marl.tex ├── marl-book-ch9-part2-deep-marl.pdf ├── marl-book-ch9-part2-deep-marl.tex ├── preamble.tex └── python-style.tex /.gitignore: -------------------------------------------------------------------------------- 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