Survey
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
* Your assessment is very important for improving the workof artificial intelligence, which forms the content of this project
Ecological interface design wikipedia , lookup
Intelligence explosion wikipedia , lookup
Embodied cognitive science wikipedia , lookup
Philosophy of artificial intelligence wikipedia , lookup
Personal knowledge base wikipedia , lookup
Ethics of artificial intelligence wikipedia , lookup
Existential risk from artificial general intelligence wikipedia , lookup
Logic programming wikipedia , lookup
The Further Education and Training Awards Council (FETAC) was set up as a statutory body on 11 June 2001 by the Minister for Education and Science. Under the Qualifications (Education & Training) Act, 1999, FETAC now has responsibility for making awards previously made by NCVA. Module Descriptor Knowledge Based Systems Level 6 C30142 www.fetac.ie 1 Title Knowledge Based Systems 2 Code C30142 3 Level 6 4 Value 2 credits 5 Purpose This module has been designed to enable the learner to acquire the programming concepts and techniques associated with Intelligent Knowledge Based environments. The module is language independent and includes only those concepts that are unique to both the declarative and procedural style of programming. This is an elective module on the Advanced Certificate in Networks and Software Systems at Level 6. 6 7 8 Preferred Entry Level Special Requirements Level 5 Certificate in or equivalent. The learner should have successfully completed FETAC Computer Architecture and Systems (C20012) or Information Systems (B20015) or equivalent. General Aims This module aims to enable the learner to: 8.1 understand the need for a coherent approach to logic programming 8.2 demonstrate an understanding of the concepts of logical program design 8.3 develop good programming techniques and appreciate the need for a deliberated approach to logic program design 8.4 appreciate the problems inherent in interpreting natural language input to a computer 8.5 understand that programmable artificial intelligence focuses on activities that cannot be treated at a simple algorithmic level 8.6 code and test a series of short structured logic problems 8.7 write and test a specific logic problem. 1 9 Units Unit 1 Unit 2 Unit 3 Unit 4 10 Natural Language and Programmable Logic Data Structures, Data Variables and Semantic Logic Knowledge Based Systems and Artificial Intelligence Intelligent Knowledge Based Systems and Expert Systems Specific Learning Outcomes Unit 1 Natural Language and Programmable Logic The learner should be able to: 10.1.1 specify the factors for and against using natural language in a knowledge based system 10.1.2 identify logic languages as being rules-based with built in pattern matching and backtracking facilities 10.1.3 recognize that knowledge and metaknowledge can interact with strategic rules to help solve logic problems 10.1.4 list the criteria involved in good logic programming 10.1.5 explain what are goals 10.1.6 explain the term backtracking and its use in logic programs 10.1.7 generate and implement a set of logic rules as facts 10.1.8 generate and implement a set of logical predicates 10.1.9 identify predicates as a series of factual arguments 10.1.10 generate and implement a set logical clauses 10.1.11 identify clauses as a set of rules and predicates 10.1.12 specify predicates, rules, domains and goals as elements of a logic program 10.1.13 describe what are instantiated variables. Unit 2 Data Structures, Data Variables and Semantic Logic The learner should be able to: 10.2.1 specify the requirements of a logic program 10.2.2 understand the need for a procedural approach to logic programming 10.2.3 distinguish between backward and forward chaining 10.2.4 code a procedure as a set of clauses about the same relation 2 10.2.5 write a program that will execute the procedure as a set of goals or objectives 10.2.6 define a list of factual rules as facts 10.2.7 code and initiate a list of elements with associate members 10.2.8 identify the importance of the head and tail of a structured list 10.2.9 write a short program that will execute a structured list 10.2.10 perform a search on a structured list using a member program 10.2.11 add and delete elements of a structured list 10.2.12 perform logical checks on a structured list 10.2.13 sort a structured list using a quick sort, bubble sort or insertion sort algorithm 10.2.14 demonstrate the use of debugging to trace missed goals 10.2.15 implement the fail goal using negation by failure 10.2.16 identify unnecessary backtracking in a logic program 10.2.17 eliminate unnecessary backtracking using a cut procedure. Unit 3 Knowledge Based Systems and Artificial Intelligence The learner should be able to: 10.3.1 explain why artificial intelligence looks at all activities which cannot be treated at a simple, standard, algorithmic level 10.3.2 explain how an artificial intelligence system can bypass the normal linguistic process 10.3.3 outline with examples how the Turing Test of machine intelligence works e.g., ELIZA, ALICE, GENERAL PROBLEM SOLVER, Frudes 10.3.4 explain the term Mixed Initiative System (MIS) 10.3.5 list examples of artificial intelligence as mailbox, handwriting recognition, multi modality 10.3.6 identify artificial intelligence languages as both procedural and declarative. Unit 4 Intelligent Knowledge Based Systems and Expert Systems The learner should be able to: 10.4.1 illustrate and outline the components of a general expert system 10.4.2 describe the architecture of an intelligent knowledge based system (IKBS) 3 11 10.4.3 distinguish between an intelligent knowledge based system and an informational database system 10.4.4 define a knowledge based system as a component of an expert system 10.4.5 describe the merits of input devices in a knowledge based system such as mouse, trackball, touch-screen, light pen 10.4.6 evaluate a short case study of a suitable working expert system 10.4.7 explain how object oriented programming (OOP) can be a useful tool in developing an intelligent knowledge based system 10.4.8 describe the role of an inference engine 10.4.9 explain what is an intelligent front end processor (IFE) 10.4.10 list the tasks that an IFE processor can perform. Assessment Summary Project Written Examination 11.1 Technique Details Project Code and test a specified logic program based on the short assignments developed in the specific learning outcomes. 11.2 Technique Written Examination Format 6 structured questions based on all the units. 5 Questions to be answered. 12 Performance Criteria 12.1 Project 12.2 Written Examination 13 Grading 50% 50% The performance criteria for each component of the project should be detailed in the accompanying Individual Candidate Marking Sheet. The Assessor must devise an examination paper and an outline marking scheme. These must be made available to the external Authenticator. Pass Merit Distinction 50 - 64% 65 - 79% 80 - 100% 4 Knowledge Based Systems Individual Candidate Marking Sheet 1 C30142 Project 50% Candidate Name: _________________________________ PPSN: ____________________ Centre: _________________________________________________ Centre No: _________ Maximum Mark Performance Criteria Candidate Mark Note to Assessor: List the performance criteria and outline marking scheme used to assess the project completed by the candidate. Total WEIGHED TOTAL (= TOTAL ÷2) 100 50% Assessor Signature: _______________________________________ Date: ______________ External Authenticator’s Signature: _________________________ Date: ______________ 5 Knowledge Based Systems Individual Candidate Marking Sheet 2 C30142 Written Examination 50% Candidate Name: _________________________________ PPSN: ____________________ Centre: _________________________________________________ Centre No: _________ Maximum Mark Performance Criteria Candidate Mark 5 questions to be answered Question (…) 20 Question (…) 20 Question (…) 20 Question (…) 20 Question (…) 20 Total 100 WEIGHED TOTAL (= TOTAL ÷ 2) 50% Assessor Signature: ________________________________________ Date: ____________ External Authenticator’s Signature: __________________________ Date: ____________ 6 FETAC Module Results Summary Sheet Module: Knowledge Based Systems Module Code: C30142 Elements of Assessment Project Maximum Marks per element of assessment Candidate Name Exam No. 50% Signed: Assessor: _________________________________________________ Date: ___________ This sheet is for teachers/Assessors to record the overall marks of individual candidates. It should be retained in the centre. The marks awarded should be transferred to the official FETAC Module Results Sheet issued to centres before the visit of the external Authenticator. 7 Written Examination 50% % Marks 100% Grade* Grade* D: 80 - 100% M: 65 - 79% P: 50 - 64% U: 0 - 49% W: candidates entered who did not present for assessment