4rdhendu/aima-python

Python implementation of algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

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aima-python

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.

Python 3.4

This code is in Python 3.4 (Python 3.5, also works, but Python 2.x does not). You can install the latest Python version or use a browser-based Python interpreter such as repl.it.

Structure of the Project

When complete, this project will have Python code for all the pseudocode algorithms in the book. For each major topic, such as logic, we will have the following three files in the main branch:

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

Index of Algorithms

Here is a table of algorithms, the figure, name of the code in the book and in the repository, and the file where they are implemented in the code. 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 project describes all the algorithms from the book.

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

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
4.9	vacumm_world	search.py
4.23	one_dim_state_space	search.py
6.1	australia_map	search.py
7.13	wumpus_world_inference	logic.py
7.16	horn_clauses_KB	logic.py
17.1	sequential_decision_environment	mdp.py
18.2	waiting_decision_tree	learning.py

Acknowledgements

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, and @reachtarunhere.