Artificial Intelligence: A Modern Approach, in Python3

pip install aima3==1.0.11


aima-python Build Status Binder

Python code for the book Artificial Intelligence: A Modern Approach. You can use this in conjunction with a course on AI, or for study on your own. We're looking for solid contributors to help.

Structure of the Project

When complete, this project will have Python implementations for all the pseudocode algorithms in the book, as well as tests and examples of use. For each major topic, such as nlp (natural language processing), we provide the following files:

  • Implementations of all the pseudocode algorithms, and necessary support functions/classes/data.
  • tests/ A lightweight test suite, using assert statements, designed for use with py.test, but also usable on their own.
  • nlp.ipynb: A Jupyter (IPython) notebook that explains and gives examples of how to use the code.
  • nlp_apps.ipynb: A Jupyter notebook that gives example applications of the code.

Python 3.4 and up

This code requires Python 3.4 or later, and does not run in Python 2. You can install Python or use a browser-based Python interpreter such as You can run the code in an IDE, or from the command line with python -i where the -i option puts you in an interactive loop where you can run Python functions. See for instructions on setting up your own Jupyter notebook environment, or run the notebooks online with

Index of Algorithms

Here is a table of algorithms, the figure, name of the algorithm in the book and in the repository, and the file where they are implemented in the repository. This chart was made for the third edition of the book and is being updated for the upcoming fourth edition. Empty implementations are a good place for contributors to look for an issue. The aima-pseudocode project describes all the algorithms from the book. An asterisk next to the file name denotes the algorithm is not fully implemented. Another great place for contributors to start is by adding tests and writing on the notebooks. You can see which algorithms have tests and notebook sections below. If the algorithm you want to work on is covered, don't worry! You can still add more tests and provide some examples of use in the notebook!

Figure Name (in 3rd edition) Name (in repository) File Tests Notebook
2 Random-Vacuum-Agent RandomVacuumAgent Done
2 Model-Based-Vacuum-Agent ModelBasedVacuumAgent Done
2.1 Environment Environment Done Included
2.1 Agent Agent Done Included
2.3 Table-Driven-Vacuum-Agent TableDrivenVacuumAgent
2.7 Table-Driven-Agent TableDrivenAgent
2.8 Reflex-Vacuum-Agent ReflexVacuumAgent Done
2.10 Simple-Reflex-Agent SimpleReflexAgent
2.12 Model-Based-Reflex-Agent ReflexAgentWithState
3 Problem Problem Done
3 Node Node Done
3 Queue Queue Done
3.1 Simple-Problem-Solving-Agent SimpleProblemSolvingAgent
3.2 Romania romania Done Included
3.7 Tree-Search tree_search Done
3.7 Graph-Search graph_search Done
3.11 Breadth-First-Search breadth_first_search Done Included
3.14 Uniform-Cost-Search uniform_cost_search Done Included
3.17 Depth-Limited-Search depth_limited_search Done
3.18 Iterative-Deepening-Search iterative_deepening_search Done
3.22 Best-First-Search best_first_graph_search Done
3.24 A*-Search astar_search Done Included
3.26 Recursive-Best-First-Search recursive_best_first_search Done
4.2 Hill-Climbing hill_climbing Done
4.5 Simulated-Annealing simulated_annealing Done
4.8 Genetic-Algorithm genetic_algorithm Done Included
4.11 And-Or-Graph-Search and_or_graph_search Done
4.21 Online-DFS-Agent online_dfs_agent
4.24 LRTA*-Agent LRTAStarAgent Done
5.3 Minimax-Decision minimax_decision Done Included
5.7 Alpha-Beta-Search alphabeta_search Done Included
6 CSP CSP Done Included
6.3 AC-3 AC3 Done
6.5 Backtracking-Search backtracking_search Done Included
6.8 Min-Conflicts min_conflicts Done
6.11 Tree-CSP-Solver tree_csp_solver Done Included
7 KB KB Done Included
7.1 KB-Agent KB_Agent Done
7.7 Propositional Logic Sentence Expr Done
7.10 TT-Entails tt_entails Done
7.12 PL-Resolution pl_resolution Done Included
7.14 Convert to CNF to_cnf Done
7.15 PL-FC-Entails? pl_fc_resolution Done
7.17 DPLL-Satisfiable? dpll_satisfiable Done
7.18 WalkSAT WalkSAT Done
7.20 Hybrid-Wumpus-Agent HybridWumpusAgent
7.22 SATPlan SAT_plan Done
9 Subst subst Done
9.1 Unify unify Done Included
9.3 FOL-FC-Ask fol_fc_ask Done
9.6 FOL-BC-Ask fol_bc_ask Done
9.8 Append
10.1 Air-Cargo-problem air_cargo Done
10.2 Spare-Tire-Problem spare_tire Done
10.3 Three-Block-Tower three_block_tower Done
10.7 Cake-Problem have_cake_and_eat_cake_too Done
10.9 Graphplan GraphPlan
10.13 Partial-Order-Planner
11.1 Job-Shop-Problem-With-Resources job_shop_problem Done
11.5 Hierarchical-Search hierarchical_search
11.8 Angelic-Search
11.10 Doubles-tennis double_tennis_problem
13 Discrete Probability Distribution ProbDist Done Included
13.1 DT-Agent DTAgent
14.9 Enumeration-Ask enumeration_ask Done Included
14.11 Elimination-Ask elimination_ask Done Included
14.13 Prior-Sample prior_sample Included
14.14 Rejection-Sampling rejection_sampling Done Included
14.15 Likelihood-Weighting likelihood_weighting Done Included
14.16 Gibbs-Ask gibbs_ask Done Included
15.4 Forward-Backward forward_backward Done
15.6 Fixed-Lag-Smoothing fixed_lag_smoothing Done
15.17 Particle-Filtering particle_filtering Done
16.9 Information-Gathering-Agent
17.4 Value-Iteration value_iteration Done Included
17.7 Policy-Iteration policy_iteration Done
17.9 POMDP-Value-Iteration
18.5 Decision-Tree-Learning DecisionTreeLearner Done Included
18.8 Cross-Validation cross_validation
18.11 Decision-List-Learning DecisionListLearner*
18.24 Back-Prop-Learning BackPropagationLearner Done Included
18.34 AdaBoost AdaBoost
19.2 Current-Best-Learning current_best_learning Done Included
19.3 Version-Space-Learning version_space_learning Done Included
19.8 Minimal-Consistent-Det minimal_consistent_det Done
19.12 FOIL FOIL_container Done
21.2 Passive-ADP-Agent PassiveADPAgent Done
21.4 Passive-TD-Agent PassiveTDAgent Done Included
21.8 Q-Learning-Agent QLearningAgent Done Included
22.1 HITS HITS Done Included
23 Chart-Parse Chart Done Included
23.5 CYK-Parse CYK_parse Done Included
25.9 Monte-Carlo-Localization monte_carlo_localization Done

Index of data structures

Here is a table of the implemented data structures, the figure, name of the implementation in the repository, and the file where they are implemented.

Figure Name (in repository) File
3.2 romania_map
4.9 vacumm_world
4.23 one_dim_state_space
6.1 australia_map
7.13 wumpus_world_inference
7.16 horn_clauses_KB
17.1 sequential_decision_environment
18.2 waiting_decision_tree


Many thanks for contributions over the years. I got bug reports, corrected code, and other support from Darius Bacon, Phil Ruggera, Peng Shao, Amit Patil, Ted Nienstedt, Jim Martin, Ben Catanzariti, and others. Now that the project is on GitHub, you can see the contributors who are doing a great job of actively improving the project. Many thanks to all contributors, especially @darius, @SnShine, @reachtarunhere, @MrDupin, and @Chipe1.