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- 1. Introduction to Artificial Intelligence Information for students 2000/2001 (Level 2/Level 3) Course Tutor(s): Name Office Phone Email Venky Shankararaman LC267 4351 V.Shankararaman Neil Davey LB220 4310 N.Davey Dave Smith D209 4341 D.E.Smith Vivian Ambrosiadou B301 4347 B.V.Ambrosiadou Amanda Derrick LC255 4369 A.J.Derrick Course web page: http://homepages.feis.herts.ac.uk/~2com0007 Class contact arrangements: 2 hours lecture 1 hour tutorial Course Delivery Plan: Week Title Activity Material Coursework Time 02 Problems and Search Exercises + Handout 1 10 hours 2/10 Get BFS code working Chapter 1, Chapter 3, Chapter 10 Luger 03 Uninformed Methods Exercises + Handout 1 Coursework 1 10 hours 09/10 Work on coursework Chapter 3 Luger Handed Out 04 Algorithms Exercises + Handout 1 Chapter 3 Luger 10 hours 16/10 Work on coursework 05 Informed methods and Check Point: structured Handout 1 Chapter 4, 10 hours 23/10 heuristic search search. — check ID Luger 06 Hill Climbing and Use provided code to Chapter 4 Dean, Allen, 10 hours 30/10 Simulated Annealing run some SA Aloimonos experiments 07 Genetic Algorithms Run some SA Chapter 15 Luger 10 hours 06/11 experiments 08 Adversarial Search Exercises Luger Chapter 4. Section 10 hours 13/11 4.3 09 Adversarial Search Luger Chapter 4. Section Coursework 1 10 hours 20/11 4.3 Completed 10 Overview Examples sheet Luger 2.0 — 2.2 and 10 hours 27/11 Predicate Logic, syntax and handout semantics 11 Predicate Logic Example sheet, on Luger 2.3, 6.0 and handout 10 hours 04/12 Single Proofs by resolution. unification and Unification resolution. Horn Clauses and Prolog 12 Theorem Proving in Prolog Example sheet, on Luger 6.1 and handout 10 hours 11/12 Non declarative semantics Prolog search trees/ of Prolog PROLOG practical 16 Semantic Networks Example sheet on Luger 9.0-9.3 + handout Coursework 2 10 hours 08/01 Conceptual Graphs graphical handed out representations of knowledge / Prolog practical
- 2. Week Title Activity Material Coursework Time 17 Frames Example sheet on Luger 9.4 — 9.5 10 hours 15/01 Type Hierarchy Frames + handout Prolog practical 19 Human Info. Processing Review some expert Handout 1. Coursework 2 10 hours 29/01 and Introduction to expert system applications Luger Chapter 6, Sections completed systems 6.0, and 6.1 20 Rule-based systems Exercise on writing Handout 2. Coursework 3 10 hours 05/02 rules Luger Chapter 5, Section hand out 5.3 and Chapter 6, Section 6.2 21 Phases in developing a Exercise on modeling Handout 3. 10 hours 12/02 KBS 22 CLIPS Exercise on CLIPS + CLIPS user guide 10 hours 19/02 work on coursework 23 CLIPS Exercise on CLIPS + CLIPS user guide 10 hours 26/02 work on coursework 24 Modelling Learning- Handout 1, Coursework 3 5 hours 05/03 Methods, Approaches and Chapter 13 Luger completed Terms, ID3 Algorithm Coursework 4 Handed out 25 More on Quinlan’s ID3 Understanding the ID3 Handout 2, Luger, Chapter Laboratory work 15 hours 12/03 Algorithm and software algorithm and 13 information theory by working out specific examples given by the lecturer 26 Version Space Search Practice on algorithms Handout 3, Luger, Chapter 12 hours 19/03 General to Specific Search, by using specific 13 Specific to General Search, examples given by the lecturer, understanding of the coursework 27 Machine Learning- Practice on algorithms Handout 4, Luger, Chapter Coursework 4 12 hours 26/03 Winstons Algorithms and 13 completed Candidate Elimination Algorithm 31 Machine Learning- 23/04 Revision and coursework feedback 32 Revision 30/04 Assessment method: 40 % Coursework 60% Examination The assessment for the Level 2 and Level 3 are separate with some shared components. Pass conditions: Pass overall In-course assignments: CW1 Date set: w/b 9 October Submission date: Friday 24 November by 3 pm at FEIS reception Percentage of total assessment: 16 Group or Individual: Group (pairs) Topic: Search
- 3. Target date for return of marked work: w/b 8 January CW2 Date set: w/b 8 January Submission date: Friday 2 February by 3pm at FEIS reception Percentage of total assessment: 8% Group or Individual: Individual Topic: Logic Target date for return of marked work: w/b 26 March CW3 Date set: w/b 5 February Submission date: Friday 9 March by 3pm at FEIS reception Percentage of total assessment: 8% Group or Individual: Group (pairs) Topic: Rule-Based Systems Target date for return of marked work: w/b 23 April CW4 Date set: w/b 12 March Submission date: Friday 30 March by 3pm at FEIS reception Percentage of total assessment: 8% Group or Individual: Group (pairs) Topic: Machine Learning Target date for return of marked work: w/b 23 April Study time: Total: 300 hours of which Class contact: 69 Assessment: 75 Directed study outside class time: 80 Other activities (non-assessed): 76 eg. reading, library investigations, practical exercises or revision for examination Recommended reading Essential reading Lecture hand-outs Additional reading Artificial Intelligence, Theory and Practice. Thomas Dean, James Allen and John Alloimonos, Benjamin Cummings, 1995. Luger G F and Stubblefield W A. Artificial Intelligence: Structures and Strategies for Complex Problem Solving. 1998. Addison Wesley Longman, Inc.