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Pseudocode descriptions of the algorithms from Russell And Norvig's "Artificial Intelligence - A Modern Approach"

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Pseudocode

Pseudocode descriptions of the algorithms from Russell and Norvig's Artificial Intelligence - A Modern Approach.

The file aima3e-algorithms.pdf contains all the algorithms exactly as they appear in the third edition of the book. The files listed below duplicate that information but with typography that is not as fancy. When there are differences between the third edition and fourth edition pseudocode, both versions will be shown in the files listed below. (Note: when editing pseudocode in a md/*.md file, put two spaces at the end of a line; this keeps the line separate from the following line.)

AIMA3e AIMA4e Pseudo-code (in book)
2.3 TABLE-DRIVEN-AGENT
2.4 REFLEX-VACUUM-AGENT
2.6 SIMPLE-REFLEX-AGENT
2.8 MODEL-BASED-REFLEX-AGENT
3.1 SIMPLE-PROBLEM-SOLVING-AGENT
3.7 TREE-SEARCH and GRAPH-SEARCH
3.11 BREADTH-FIRST-SEARCH
3.13 UNIFORM-COST-SEARCH
3.16 DEPTH-LIMITED-SEARCH
3.17 ITERATIVE-DEEPENING-SEARCH
3.24 RECURSIVE-BEST-FIRST-SEARCH
4.2 HILL-CLIMBING
4.5 SIMULATED-ANNEALING
4.8 GENETIC-ALGORITHM
4.11 AND-OR-GRAPH-SEARCH
4.21 ONLINE-DFS-AGENT
4.24 LRTA*-AGENT
5.3 MINIMAX-DECISION
5.7 ALPHA-BETA-SEARCH
6.3 AC-3
6.5 BACKTRACKING-SEARCH
6.8 MIN-CONFLICTS
6.11 TREE-CSP-SOLVER
7.1 KB-AGENT
7.8 TT-ENTAILS
7.9 PL-RESOLUTION
7.12 PL-FC-ENTAILS?
7.14 DPLL-SATISFIABLE?
7.15 WALKSAT
7.17 HYBRID-WUMPUS-AGENT
7.19 SATPLAN
9.1 UNIFY
9.3 FOL-FC-ASK
9.6 FOL-BC-ASK
9.8 APPEND
10.1 AIR-CARGO-TRANSPORT-PROBLEM
10.2 SPARE-TIRE-PROBLEM
10.3 BLOCKS-WORLD
10.7 HAVE-CAKE-AND-EAT-CAKE-TOO-PROBLEM
10.9 GRAPHPLAN
11.1 JOB-SHOP-SCHEDULING-PROBLEM
11.4 REFINEMENT-HIGH-LEVEL-ACTIONS
11.5 HIERARCHICAL-SEARCH
11.8 ANGELIC-SEARCH
11.10 DOUBLES-TENNIS-PROBLEM
13.1 DT-AGENT
14.9 ENUMERATION-ASK
14.10 ELIMINATION-ASK
14.12 PRIOR-SAMPLE
14.13 REJECTION-SAMPLING
14.14 LIKELIHOOD-WEIGHTING
14.15 GIBBS-ASK
15.4 FORWARD-BACKWARD
15.6 FIXED-LAG-SMOOTHING
15.17 PARTICLE-FILTERING
16.9 INFORMATION-GATHERING-AGENT
17.4 VALUE-ITERATION
17.7 POLICY-ITERATION
17.9 POMDP-VALUE-ITERATION
18.4 DECISION-TREE-LEARNING
18.7 CROSS-VALIDATION-WRAPPER
18.10 DECISION-LIST-LEARNING
18.23 BACK-PROP-LEARNING
18.33 ADABOOST
19.2 CURRENT-BEST-LEARNING
19.3 VERSION-SPACE-LEARNING
19.8 MINIMAL-CONSISTENT-DET
19.12 FOIL
21.2 PASSIVE-ADP-AGENT
21.4 PASSIVE-TD-AGENT
21.8 Q-LEARNING-AGENT
22.1 HITS
23.4 CYK-PARSE
23.5 SENTENCE-TREE
25.9 MONTE-CARLO-LOCALIZATION
29.1 POWERS-OF-2

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