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AIMA
by Artem Yankov
# AIMA

## Knowledge representation

### Semantic networks

### Description logics

### Closed-world assumption

### Nonmonotonic logics

### Truth maintenance systems

## NLP/NLU

### n-grams

### Text classification

### Information retrieval

### Information extraction

## Search

### Uninformed Search

### Informed (Heuristic Search)

### Local Search

### Constraint satisfactioin

### Adversarial Search

## Probabilistic reasoning

### Decision theory

### Full joint probability distributions

### Bayes' rule

### Bayesian networks

### Temporal (over time)

### Markov decision processes

### Game theory

## Learning

### Supervised

### Unsupervised

### Reinforcement Learning

## Reasoning

### Logical agents

### First-order logic

### Planning

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Default logic

Naive Bayes n-gram

bag of words

Question answering

FSA

HMMs

Conditional random fields

BFS

DFS

Uniform-cost search

Iterative deepening search

Bidirectional search

BFS + Eval. function

Greedy BFS

A*

Recursive BFS

SMA*

Hill climbing, genetic algorithm, tabu search

Linear programming

Convex optimization

Backtracking

Min-conflicts heuristics

Cutset conditioning

Tree decomposition

Constraint propagation

Minimax

Alpha-beta

Hybrid Bayesian networks

polytrees

Likelihood weighting

Markov chain Monte Carlo

RPMs

Hidden Markov Models

Kalman filters

dynamic Bayesian networks

Transition model

Reward function

Nash equilibria

Classification

Regression

Loss function

Cross-validation

Model-based design

Model-free design

Reflex design

Utility, Direct utility estimation, Adaptive dynamic programming, Temporal-difference

Propositional logic

WalkSAT (Local search method)

Modus Ponens

Forward chaning, Datalog

Backward chaning, Logic programming systems

Determenistic env., PDDL, State-space search, Progression, Regression, Planning graph

Nondetermenistic env., Hierarchical task network (HTN), Contingent plans, Online planning agent, Multiagent planning