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Lecture Artificial Intelligence - Chapter 20a: Statistical learning
Lecture Artificial Intelligence - Chapter 20a: Statistical learning. The main contents of this chapter include all of the following: Bayesian learning, maximum a posteriori and maximum likelihood learning, bayes net learning.
4/8/2023 10:57:04 AM +00:00
Lecture Artificial Intelligence - Chapter 18: Learning from Observations
Lecture Artificial Intelligence - Chapter 18: Learning from Observations. The main contents of this chapter include all of the following: Learning agents, inductive learning, decision tree learning, measuring learning performance.
4/8/2023 10:56:57 AM +00:00
Lecture Artificial Intelligence - Chapter 16: Rational decisions
Lecture Artificial Intelligence - Chapter 16: Rational decisions. The main contents of this chapter include all of the following: Rational preferences, utilities, money, multiattribute utilities, decision networks, value of information.
4/8/2023 10:56:44 AM +00:00
Lecture Artificial Intelligence - Chapter 15b: Speech recognition (briefly)
Lecture Artificial Intelligence - Chapter 15b: Speech recognition (briefly). The main contents of this chapter include all of the following: Speech as probabilistic inference, Speech sounds, Word pronunciation, Word sequences.
4/8/2023 10:56:31 AM +00:00
Lecture Artificial Intelligence - Chapter 15a: Temporal probability models
Lecture Artificial Intelligence - Chapter 15a: Temporal probability models. The main contents of this chapter include all of the following: Time and uncertainty; Inference: filtering, prediction, smoothing; Hidden Markov models; Kalman filters (a brief mention); Dynamic Bayesian networks; Particle filtering.
4/8/2023 10:56:24 AM +00:00
Lecture Artificial Intelligence - Chapter 14b: Inference in Bayesian networks
Lecture Artificial Intelligence - Chapter 14b: Inference in Bayesian networks. The main contents of this chapter include all of the following: Exact inference by enumeration, exact inference by variable elimination, approximate inference by stochastic simulation, approximate inference by Markov chain Monte Carlo.
4/8/2023 10:56:06 AM +00:00
Lecture Artificial Intelligence - Chapter 14a: Bayesian networks
Lecture Artificial Intelligence - Chapter 14a: Bayesian networks. The main contents of this chapter include all of the following: Bayes nets provide a natural representation for (causally induced) conditional independence, topology + CPTs = compact representation of joint distribution, Generally easy for (non)experts to construct, Canonical distributions (e.g., noisy-OR) = compact representation of CPTs, Continuous variables ⇒ parameterized distributions (e.g., linear Gaussian).
4/8/2023 10:55:59 AM +00:00
Lecture Artificial Intelligence - Chapter 13: Uncertainty
Lecture Artificial Intelligence - Chapter 13: Uncertainty. The main contents of this chapter include all of the following: Probability is a rigorous formalism for uncertain knowledge; joint probability distribution specifies probability of every atomic event; queries can be answered by summing over atomic events; for nontrivial domains; we must find a way to reduce the joint size; independence and conditional independence provide the tools.
4/8/2023 10:55:46 AM +00:00
Lecture Artificial Intelligence - Chapter 9: Inference in first-order logic
Lecture Artificial Intelligence - Chapter 9: Inference in first-order logic. The main contents of this chapter include all of the following: Reducing first-order inference to propositional inference, unification, generalized modus ponens, forward and backward chaining, logic programming, resolution.
4/8/2023 10:55:31 AM +00:00
Lecture Artificial Intelligence - Chapter 8: First-order logic
Lecture Artificial Intelligence - Chapter 8: First-order logic. The main contents of this chapter include all of the following: First-order logic: objects and relations are semantic primitives; syntax: constants, functions, predicates, equality, quantifiers; Increased expressive power: sufficient to define wumpus world; Situation calculus: conventions for describing actions and change in FOL; situation calculus: can formulate planning as inference on a situation calculus KB.
4/8/2023 10:55:15 AM +00:00
Lecture Artificial Intelligence - Chapter 7: Logical agents
Lecture Artificial Intelligence - Chapter 7: Logical agents. The main contents of this chapter include all of the following: Knowledge-based agents, wumpus world, logic in general—models and entailment, propositional (boolean) logic; equivalence, validity, satisfiability; inference rules and theorem proving.
4/8/2023 10:55:02 AM +00:00
Lecture Artificial Intelligence - Chapter 6: Game playing
Lecture Artificial Intelligence - Chapter 6: Game playing. The main contents of this chapter include all of the following: Games, Perfect play, Resource limits and approximate evaluation, Games of chance, Games of imperfect information.
4/8/2023 10:54:49 AM +00:00
Lecture Artificial Intelligence - Chapter 5: Constraint Satisfaction Problems
Lecture Artificial Intelligence - Chapter 5: Constraint Satisfaction Problems. The main contents of this chapter include all of the following: CSP examples, backtracking search for CSPs, problem structure and problem decomposition, local search for CSPs.
4/8/2023 10:54:36 AM +00:00
Lecture Artificial Intelligence - Chapter 4b: Local search algorithms
Lecture Artificial Intelligence - Chapter 4b: Local search algorithms. The main contents of this chapter include all of the following: Hill-climbing, simulated annealing, genetic algorithms (briefly), local search in continuous spaces (very briefly).
4/8/2023 10:54:21 AM +00:00
Lecture Artificial Intelligence - Chapter 4a: Informed search algorithms
Lecture Artificial Intelligence - Chapter 4a: Informed search algorithms. The main contents of this chapter include all of the following: Heuristic functions estimate costs of shortest paths, good heuristics can dramatically reduce search cost, greedy best-first search expands lowest h – incomplete and not always optimal, admissible heuristics can be derived from exact solution of relaxed problems.
4/8/2023 10:54:08 AM +00:00
Lecture Artificial Intelligence - Chapter 3: Problem solving and search
Lecture Artificial Intelligence - Chapter 3: Problem solving and search. The main contents of this chapter include all of the following: Problem-solving agents, problem types, problem formulation, example problems, basic search algorithms, informed search algorithms.
4/8/2023 10:53:55 AM +00:00
Lecture Artificial Intelligence - Chapter 2: Intelligent agents
Lecture Artificial Intelligence - Chapter 2: Intelligent agents. The main contents of this chapter include all of the following: Agents interact with environments through actuators and sensors, the agent function describes what the agent does in all circumstances, the performance measure evaluates the environment sequence, a perfectly rational agent maximizes expected performance, agent programs implement (some) agent functions, PEAS descriptions define task environments Environments are categorized along several dimensions.
4/8/2023 10:53:39 AM +00:00
Lecture Artificial Intelligence - Chapter 1: Introduce
Lecture Artificial Intelligence - Chapter 1: Introduce. This chapter presents the following content: What is AI? A brief history, the state of the art, thinking humanly: Cognitive Science,...
4/8/2023 10:53:26 AM +00:00
Lecture Compiler construction: Lesson 45 - Sohail Aslam
Lecture Compiler construction: Lesson 45 - Sohail Aslam. The main topics covered in this chapter include: basic code generation, DAG representations, detect common sub-expression elimination, node with more than one parent is common sub-expression, reordering to reduce number of generated instructions,...
4/8/2023 7:08:30 AM +00:00
Lecture Compiler construction: Lesson 44 - Sohail Aslam
Lecture Compiler construction: Lesson 44 - Sohail Aslam. The main topics covered in this chapter include: basic code generation, use registers whenever possible, a non-live value in a register can be discarded, freeing that register, address descriptor, register descriptor,...
4/8/2023 7:08:19 AM +00:00
Lecture Compiler construction: Lesson 43 - Sohail Aslam
Lecture Compiler construction: Lesson 43 - Sohail Aslam. The main topics covered in this chapter include: control flow graph - CFG, basic blocks, sequence of consecutive statements with single entry/single exit, generating CFGs, algorithm partition into basic blocks, basic block code generation,...
4/8/2023 7:08:13 AM +00:00
Lecture Compiler construction: Lesson 42 - Sohail Aslam
Lecture Compiler construction: Lesson 42 - Sohail Aslam. The main topics covered in this chapter include: code generation, the code generation problem task of mapping intermediate code to machine code; memory management mapping names to data objects in the run-time system, target assembly language,...
4/8/2023 7:08:06 AM +00:00
Lecture Compiler construction: Lesson 41 - Sohail Aslam
Lecture Compiler construction: Lesson 41 - Sohail Aslam. The main topics covered in this chapter include: flow-of-control statements, semantic actions, semantic actions in YACC, the syntax-directed translation statements can be conveniently specified in YACC,...
4/8/2023 7:07:58 AM +00:00
Lecture Compiler construction: Lesson 40 - Sohail Aslam
Lecture Compiler construction: Lesson 40 - Sohail Aslam. The main topics covered in this chapter include: boolean expressions, backpatching consider again, the boolean expression, semantic actions, flow-of-control statements, backpatching to translate flow-of-control statements in one pass,...
4/8/2023 7:07:49 AM +00:00
Lecture Compiler construction: Lesson 39 - Sohail Aslam
Lecture Compiler construction: Lesson 39 - Sohail Aslam. The main topics covered in this chapter include: boolean expressions, flow of control method, the easiest way to implement syntax-directed definitions is to use two passes, the semantic action,...
4/8/2023 7:07:42 AM +00:00
Lecture Compiler construction: Lesson 38 - Sohail Aslam
Lecture Compiler construction: Lesson 38 - Sohail Aslam. The main topics covered in this chapter include: three-address statement types, assignment statement, copy statement, unconditional jump, flow-of-control statements, discuss semantic rules for boolean expressions shortly,...
4/8/2023 7:07:32 AM +00:00
Lecture Compiler construction: Lesson 37 - Sohail Aslam
Lecture Compiler construction: Lesson 37 - Sohail Aslam. The main topics covered in this chapter include: representing linear codes, three-address codes, simple array of quadruples, array of pointers to quads, linked list of quads, flow-of-control statements, symbolically labeled,...
4/8/2023 7:07:26 AM +00:00
Lecture Compiler construction: Lesson 36 - Sohail Aslam
Lecture Compiler construction: Lesson 36 - Sohail Aslam. The main topics covered in this chapter include: three-address code, absence of destructive operators gives the compiler freedom to reuse names and values, syntax-directed translation schemes, assignment statement,...
4/8/2023 7:07:15 AM +00:00
Lecture Compiler construction: Lesson 35 - Sohail Aslam
Lecture Compiler construction: Lesson 35 - Sohail Aslam. The main topics covered in this chapter include: IR taxonomy, IRs fall into three organizational categories, parse trees are graphs that represent source-code form of the program, Abstract Syntax Trees (AST) retains the essential structure of the parse tree but eliminates extraneous nodes,...
4/8/2023 7:07:08 AM +00:00
Lecture Compiler construction: Lesson 34 - Sohail Aslam
Lecture Compiler construction: Lesson 34 - Sohail Aslam. The main topics covered in this chapter include: intermediate representations (IR), compilers organized as a series of passes, compilers use some internal form– an IR –to represent the code being analysed and translated,...
4/8/2023 7:06:58 AM +00:00