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<a href="http://aima.cs.berkeley.edu/"><img src="https://raw.githubusercontent.com/aimacode/aima-python/master/images/aima_logo.png"></a><br><br>
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# `aima-python` [](https://travis-ci.org/aimacode/aima-python) [](http://mybinder.org/repo/aimacode/aima-python)
Python code for the book *[Artificial Intelligence: A Modern Approach](http://aima.cs.berkeley.edu).* You can use this in conjunction with a course on AI, or for study on your own. We're looking for [solid contributors](https://github.com/aimacode/aima-python/blob/master/CONTRIBUTING.md) to help.
This code is in Python 3.4 (Python 3.5 and later also works, but Python 2.x does not). You can [install the latest Python version](https://www.python.org/downloads) or use a browser-based Python interpreter such as [repl.it](https://repl.it/languages/python3).
You can run the code in an IDE, or from the command line with `python -i filename.py` where the `-i` option puts you in an interactive loop where you can run Python functions.
In addition to the `filename.py` files, there are also `filename.ipynb` files, which are Jupyter (formerly IPython) notebooks. You can read these notebooks, and you can also run the code embedded with them. See [jupyter.org](http://jupyter.org/) for instructions on setting up a Jupyter notebook environment. Some modules also have `filename_apps.ipynb` files, which are notebooks for applications of the module.
When complete, this project will have Python code for all the pseudocode algorithms in the book. For each major topic, such as `nlp`, we will have the following three files in the main branch:
- `nlp.py`: Implementations of all the pseudocode algorithms, and necessary support functions/classes/data.
- `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.
- `tests/test_nlp.py`: A lightweight test suite, using `assert` statements, designed for use with [`py.test`](http://pytest.org/latest/), but also usable on their own.
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 needs to be updated for the upcoming fourth edition. Empty implementations are a good place for contributors to look for an issue. The [aima-pseudocode](https://github.com/aimacode/aima-pseudocode) project describes all the algorithms from the book. An asterisk next to the file name denotes the algorithm is not fully implemented.
| **Figure** | **Name (in 3<sup>rd</sup> edition)** | **Name (in repository)** | **File** | **Tests**
|:--------|:-------------------|:---------|:-----------|:-------|
| 2.1 | Environment | `Environment` | [`agents.py`][agents] | Done |
| 2.1 | Agent | `Agent` | [`agents.py`][agents] | Done |
| 2.3 | Table-Driven-Vacuum-Agent | `TableDrivenVacuumAgent` | [`agents.py`][agents] | |
| 2.7 | Table-Driven-Agent | `TableDrivenAgent` | [`agents.py`][agents] | |
| 2.8 | Reflex-Vacuum-Agent | `ReflexVacuumAgent` | [`agents.py`][agents] | Done |
| 2.10 | Simple-Reflex-Agent | `SimpleReflexAgent` | [`agents.py`][agents] | |
| 2.12 | Model-Based-Reflex-Agent | `ReflexAgentWithState` | [`agents.py`][agents] | |
| 3 | Problem | `Problem` | [`search.py`][search] | Done |
| 3 | Node | `Node` | [`search.py`][search] | Done |
| 3 | Queue | `Queue` | [`utils.py`][utils] | Done |
| 3.1 | Simple-Problem-Solving-Agent | `SimpleProblemSolvingAgent` | [`search.py`][search] | |
| 3.2 | Romania | `romania` | [`search.py`][search] | Done |
| 3.7 | Tree-Search | `tree_search` | [`search.py`][search] | Done |
| 3.7 | Graph-Search | `graph_search` | [`search.py`][search] | Done |
| 3.11 | Breadth-First-Search | `breadth_first_search` | [`search.py`][search] | Done |
| 3.14 | Uniform-Cost-Search | `uniform_cost_search` | [`search.py`][search] | Done |
| 3.17 | Depth-Limited-Search | `depth_limited_search` | [`search.py`][search] | Done |
| 3.18 | Iterative-Deepening-Search | `iterative_deepening_search` | [`search.py`][search] | Done |
| 3.22 | Best-First-Search | `best_first_graph_search` | [`search.py`][search] | Done |
| 3.24 | A\*-Search | `astar_search` | [`search.py`][search] | Done |
| 3.26 | Recursive-Best-First-Search | `recursive_best_first_search` | [`search.py`][search] | Done |
| 4.2 | Hill-Climbing | `hill_climbing` | [`search.py`][search] | Done |
| 4.5 | Simulated-Annealing | `simulated_annealing` | [`search.py`][search] | Done |
| 4.8 | Genetic-Algorithm | `genetic_algorithm` | [`search.py`][search] | Done |
| 4.11 | And-Or-Graph-Search | `and_or_graph_search` | [`search.py`][search] | Done |
| 4.21 | Online-DFS-Agent | `online_dfs_agent` | [`search.py`][search] | |
| 4.24 | LRTA\*-Agent | `LRTAStarAgent` | [`search.py`][search] | Done |
| 5.3 | Minimax-Decision | `minimax_decision` | [`games.py`][games] | Done |
| 5.7 | Alpha-Beta-Search | `alphabeta_search` | [`games.py`][games] | Done |
| 6 | CSP | `CSP` | [`csp.py`][csp] | Done |
| 6.3 | AC-3 | `AC3` | [`csp.py`][csp] | Done |
| 6.5 | Backtracking-Search | `backtracking_search` | [`csp.py`][csp] | Done |
| 6.8 | Min-Conflicts | `min_conflicts` | [`csp.py`][csp] | Done |
| 6.11 | Tree-CSP-Solver | `tree_csp_solver` | [`csp.py`][csp] | Done |
| 7 | KB | `KB` | [`logic.py`][logic] | Done |
| 7.1 | KB-Agent | `KB_Agent` | [`logic.py`][logic] | Done |
| 7.7 | Propositional Logic Sentence | `Expr` | [`logic.py`][logic] | Done |
| 7.10 | TT-Entails | `tt_entails` | [`logic.py`][logic] | Done |
| 7.12 | PL-Resolution | `pl_resolution` | [`logic.py`][logic] | Done |
| 7.14 | Convert to CNF | `to_cnf` | [`logic.py`][logic] | Done |
| 7.15 | PL-FC-Entails? | `pl_fc_resolution` | [`logic.py`][logic] | Done |
| 7.17 | DPLL-Satisfiable? | `dpll_satisfiable` | [`logic.py`][logic] | Done |
| 7.18 | WalkSAT | `WalkSAT` | [`logic.py`][logic] | Done |
| 7.22 | SATPlan | `SAT_plan` | [`logic.py`][logic] | Done |
| 9 | Subst | `subst` | [`logic.py`][logic] | Done |
| 9.1 | Unify | `unify` | [`logic.py`][logic] | Done |
| 9.3 | FOL-FC-Ask | `fol_fc_ask` | [`logic.py`][logic] | Done |
| 9.6 | FOL-BC-Ask | `fol_bc_ask` | [`logic.py`][logic] | Done |
| 9.8 | Append | | | |
| 10.1 | Air-Cargo-problem | `air_cargo` | [`planning.py`][planning] | Done |
| 10.2 | Spare-Tire-Problem | `spare_tire` | [`planning.py`][planning] | Done |
| 10.3 | Three-Block-Tower | `three_block_tower` | [`planning.py`][planning] | Done |
| 10.7 | Cake-Problem | `have_cake_and_eat_cake_too` | [`planning.py`][planning] | Done |
| 10.9 | Graphplan | `GraphPlan` | [`planning.py`][planning] | |
| 10.13 | Partial-Order-Planner | | | |
| 11.1 | Job-Shop-Problem-With-Resources | `job_shop_problem` | [`planning.py`][planning] | Done |
| 11.5 | Hierarchical-Search | `hierarchical_search` | [`planning.py`][planning] | |
| 11.8 | Angelic-Search | | | |
| 11.10 | Doubles-tennis | `double_tennis_problem` | [`planning.py`][planning] | |
| 13 | Discrete Probability Distribution | `ProbDist` | [`probability.py`][probability] | Done |
| 13.1 | DT-Agent | `DTAgent` | [`probability.py`][probability] | |
| 14.9 | Enumeration-Ask | `enumeration_ask` | [`probability.py`][probability] | Done |
| 14.11 | Elimination-Ask | `elimination_ask` | [`probability.py`][probability] | Done |
| 14.13 | Prior-Sample | `prior_sample` | [`probability.py`][probability] | |
| 14.14 | Rejection-Sampling | `rejection_sampling` | [`probability.py`][probability] | Done |
| 14.15 | Likelihood-Weighting | `likelihood_weighting` | [`probability.py`][probability] | Done |
| 14.16 | Gibbs-Ask | `gibbs_ask` | [`probability.py`][probability] | |
| 15.4 | Forward-Backward | `forward_backward` | [`probability.py`][probability] | Done |
| 15.6 | Fixed-Lag-Smoothing | `fixed_lag_smoothing` | [`probability.py`][probability] | Done |
| 15.17 | Particle-Filtering | `particle_filtering` | [`probability.py`][probability] | Done |
| 16.9 | Information-Gathering-Agent | | |
| 17.4 | Value-Iteration | `value_iteration` | [`mdp.py`][mdp] | Done |
| 17.7 | Policy-Iteration | `policy_iteration` | [`mdp.py`][mdp] | Done |
| 18.5 | Decision-Tree-Learning | `DecisionTreeLearner` | [`learning.py`][learning] | Done |
| 18.8 | Cross-Validation | `cross_validation` | [`learning.py`][learning] | |
| 18.11 | Decision-List-Learning | `DecisionListLearner` | [`learning.py`][learning]\* | |
| 18.24 | Back-Prop-Learning | `BackPropagationLearner` | [`learning.py`][learning] | Done |
| 18.34 | AdaBoost | `AdaBoost` | [`learning.py`][learning] | |
| 19.2 | Current-Best-Learning | `current_best_learning` | [`knowledge.py`](knowledge.py) | Done |
| 19.3 | Version-Space-Learning | `version_space_learning` | [`knowledge.py`](knowledge.py) | Done |
| 19.8 | Minimal-Consistent-Det | `minimal_consistent_det` | [`knowledge.py`](knowledge.py) | Done |
| 19.12 | FOIL | `FOIL_container` | [`knowledge.py`](knowledge.py) | Done |
| 21.2 | Passive-ADP-Agent | `PassiveADPAgent` | [`rl.py`][rl] | Done |
| 21.4 | Passive-TD-Agent | `PassiveTDAgent` | [`rl.py`][rl] | Done |
| 21.8 | Q-Learning-Agent | `QLearningAgent` | [`rl.py`][rl] | Done |
| 22.1 | HITS | `HITS` | [`nlp.py`][nlp] | Done |
| 23.5 | CYK-Parse | `CYK_parse` | [`nlp.py`][nlp] | Done |
| 25.9 | Monte-Carlo-Localization| `monte_carlo_localization` | [`probability.py`][probability] | 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 | [`search.py`][search] |
| 4.9 | vacumm_world | [`search.py`][search] |
| 4.23 | one_dim_state_space | [`search.py`][search] |
| 6.1 | australia_map | [`search.py`][search] |
| 7.13 | wumpus_world_inference | [`logic.py`][logic] |
| 7.16 | horn_clauses_KB | [`logic.py`][logic] |
| 17.1 | sequential_decision_environment | [`mdp.py`][mdp] |
| 18.2 | waiting_decision_tree | [`learning.py`][learning] |
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](https://github.com/aimacode/aima-python/graphs/contributors) who are doing a great job of actively improving the project. Many thanks to all contributors, especially @darius, @SnShine, @reachtarunhere, @MrDupin, and @Chipe1.
<!---Reference Links-->
[agents]:../master/agents.py
[csp]:../master/csp.py
[games]:../master/games.py
[grid]:../master/grid.py
[knowledge]:../master/knowledge.py
[learning]:../master/learning.py
[logic]:../master/logic.py
[mdp]:../master/mdp.py
[nlp]:../master/nlp.py
[planning]:../master/planning.py
[probability]:../master/probability.py
[rl]:../master/rl.py
[search]:../master/search.py
[utils]:../master/utils.py
[text]:../master/text.py