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WeekIDNameDateReadingTopicNotesLinks
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10Mon. Lec.1/22/2018Negnevitsky 1 (All of it)
Russel and Norvig 1.2-1.3
Role call for instructor initiated drop policy, syllabus, introduction,
rationality, conciousness
First day of classes
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1-Tues. Lab1/23/2018
No lab, watch Star Trek TNG 2x9 The Measure of a Man on your own time
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11Wed. Lec.1/24/2018Negnevitsky Chapter 1.1, emphasis on
Turing test
Russel and Norvig 1.1-1.1.4
Computing Machinery and Intelligence [1]		Jigsaw on Computing Machinery and IntelligenceKahoot!: Computing Machinery and Intelligence
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22Mon. Lec.1/29/2018Negnevitsky 2.1-2.5
Russel and Norvig 8.1-8.4
Review FOL logic from Discrete
Structures		Intelligent agents and first-order (predicate) logicKahoot!: Intelligent agents
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2-Tues. Lab1/30/2018Negnevitsky 2.1-2.2
Russel and Norvig 2.1-2.4		Lab 0: A simple reflex agent and performance metrics
https://github.com/DrAlbertCruz/CMPS-356-Lab-0
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23Wed. Lec.1/31/2018Negnevitsky 2.2First order logic, relationship to expert systems
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34Mon. Lec.2/5/2018Star Trek 2x24, The Ultimate Computer [2]Watch Star TrekHW set 1 due
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3-Tues. Lab2/6/2018Negnevitsky 2.6.1Lab 1: Backward chaining and tracing in Prologhttps://github.com/DrAlbertCruz/CMPS-356-Lab-1
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35Wed. Lec.2/7/2018Negnevitsky 2.6
Russel and Norvig 3.4-3.4.3, 9.3		Backward chaining and forward chainingKahoot!: Expert systems
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46Mon. Lec.2/12/2018Negnevitsky 3-3.1Review of probability, probability as a logic, Bayes ruleHW set 2 due, Kahoot!: Inference with FOL
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4-Tues. Lab2/13/2018Negnevitsky example on MEDIA AdvisorLab 2: MEDIA Advisor in Prologhttps://github.com/DrAlbertCruz/CMPS-356-Lab-2
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47Wed. Lec.2/14/2018Russel and Norvig 13-13.2Examples of Bayes rule, Bayes biasKahoot!: Probability quiz
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58Mon. Lec.2/19/2018Negnevitsky 3.5
Russel and Norvig 14.7		Likelihood of sufficiency and liklihood of necessityHW set 3 due, Kahoot!: 3 Var. Joint Probabilities
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5-Tues. Lab2/20/2018No new readingLab 3: Uncertainty factors in prologNo git, lab manual only
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59Wed. Lec.2/21/2018No new readingMidterm I review
http://cs.csubak.edu/~acruz/CMPS3560/cmps_3560_midterm_review_2018.pdf
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6-Mon. Lec.2/26/2018Nevnevitsky 3.6Examples of LS/LN, Measures of belief and disbeliefHW set 4 due, Kahoot!: 3 Var. Bayes http://cs.csubak.edu/~acruz/CMPS3560/cmps_3560_LSLN_examples_cf.pdf
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6-Tues. Lab2/27/2018No new readingMidterm I during lab period1 page cheat sheet front and back
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6-Wed. Lec.2/28/2018No new readingMidterm I debriefExam solutions not given out, please come to class
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710Mon. Lec.3/5/2018Negnevitsky 4.1, 4.3
Russel and Norvig 8.1.2, 14.7.3		Introduction to fuzzy logic, linguistic variables and hedgesKahoot!: CMPS 3560: LS and LN
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7-Tues. Lab3/6/2018Negnevitsky 4.3Lab 4: Fuzzy expert systems in PrologNo git, lab manual only
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711Wed. Lec.3/7/2018Negnevitsky 4.2, 4.4-4.5Fuzzy sets, operations on fuzzy sets, monotonic inferenceKahoot!: Logical paradoxes
http://cs.csubak.edu/~acruz/CMPS3560/cmps_3560_Fuzzy_ops_Monotonic_Selection.pdf
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812Mon. Lec.3/12/2018Negnevitsky 4.6.1Mamdani inference with examplesHW set 5 due, Kahoot!: CMPS 3560: Monotonic
inference		http://cs.csubak.edu/~acruz/CMPS3560/cmps_3560_fuzzy_mamdani.pdf
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8-Tues. Lab3/13/2018No new readingLab 5: Fuzzy toolbox in MATLABNo git, lab manual only
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813Wed. Lec.3/14/2018Negnevitsky 4.6.2Sugeno inference with examplesKahoot!: CMPS 3560: Monotonic inference
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914Mon. Lec.3/19/2018Negnevtistky 6.1-6.2
Russel and Norvig 18-18.2		Introduction to the brain, neurons, perceptronHW set 6 due, Kahoot!: CMPS 3560: Perceptron
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9-Tues. Lab3/20/2018Negnevitsky 6.3
Russel and Norvig 18.7-18.7.2		Lab 6: Perceptron learning algorithmFork your lab 0
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915Wed. Lec.3/21/2018No new readingLinear separability, bias terms, feature scaling
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10-Mon. Lec.3/26/2018SPRING BREAK - NO CLASS
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10-Tues. Lab3/27/2018SPRING BREAK - NO CLASS
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10-Wed. Lec.3/28/2018SPRING BREAK - NO CLASS
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11-Mon. Lec.4/2/2018No new readingMidterm II review
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11-Tues. Lab4/3/2018No new readingMidterm II during lab periodHW set 7 due
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11-Wed. Lec.4/4/2018Revisit Negnevitsky 6.3Introduction to backpropagationKahoot!: CMPS 3620: Perceptron full dataset
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1216Mon. Lec.4/9/2018No new readingIntroduction to backpropagation (Cont.)Kahoot!: CMPS 3560: ANN Feedforward
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12-Tues. Lab4/10/2018Russel and Norvig 18.7.4Lab 7: Multilayer perceptron and backpropagationKahoot!: CMPS 3560: ANN Backpropagation
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1217Wed. Lec.4/11/2018Revisit Russel and Norvig 18.7.4Midterm II debriefExam solutions not given out, please come to class
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1318Mon. Lec.4/16/2018Negnevitsky 6.4Examples of backpropagation in classHW set 8 due
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13-Tues. Lab4/17/2018No new readingLab 7 continued
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1319Wed. Lec.4/18/2018Negnevitsky 6.5Accellerating backpropagationKahoot!: CMPS 3560: Vanishing gradient
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1420Mon. Lec.4/23/2018Negnevitsky 7.1-7.3Introduction to evolutionary computationHW set 9 due, CMPS 3560: Gradient descent and
backpropagation
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14-Tues. Lab4/24/2018Negnevitsky 7.4-7.5Lab 8: Genetic algorithms and the max ones problem
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1421Wed. Lec.4/25/2018No new readingMutation, crossover, selection, elistism
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1522Mon. Lec.4/30/2018Negnevitsky 7.6Introduction to evolutionary strategiesHW set 10 due, Kahoot!: CMPS 3560: Genetic
algorithms and max ones
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15-Tues. Lab5/1/2018No new readingLab 9: (1+1) Evolutionary strategies and trend line fitting
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1523Wed. Lec.5/2/2018Negnevitsky 7.7Introduction to genetic programming
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1624Mon. Lec.5/7/2018No new readingFinal review
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16-Tues. Lab5/8/2018No new readingFinal exam in lab session
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1625Wed. Lec.5/9/2018No new readingNo classHW set 11 due
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Final Exam-Final Exam
Held during lab in week 16 because I have to leave country for a conference
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