MOST LEARNED HUMAN EXPERIENCE .
MANY TIMES A PROBLEM HAS NO SIMPLE SOLUTION AT A GIVEN REASONING LEVEL ; ABSTRACTING FROM THAT LEVEL ALLOWS ONE TO ARGUE ABOUT THE REASONING PROCESS ITSELF AND GIVES RISE TO SO-CALLED META-REASONING . META-REASONING DEALS WITH TWO TYPES OF PROBLEMS : EXTENDING INFERENCE TECHNIQUES FOR FINDING CONCEPTUAL SOLUTIONS TO PROBLEMS , AND REASONING ABOUT INFERENCE TECHNIQUES OR RULES FOR MORE EFFICIENT EXPLOITATION OF THESE INFERENCE RULES .
THE ADVANCED GENERATION OF KBS APPLICATIONS WILL BE EXPECTED TO EXPLOIT THE LESSONS OF FIRST GENERATION ATTEMPTS ( 3.1.1 ) , THE FRUITS OF KRS AND INFERENCE RESEARCH ( 3.1.3 ) , THE TOOLS OF KNOWLEDGE AND ACQUISITION MANIPULATION ( ) , THE LATEST LANGUAGES AND ENGINES ( AND ) , THE FRUITS OF NATURAL LANGUAGE PROCESSING RESEARCH ( 3.1.2 ) , AND THE FRUITS OF THE EXTERNAL INTERFACES PROGRAMME ( 3.2 ) FOR HANDLING SOUND AND IMAGES .
. LEARNING TECHNIQUES
DESCRIPTION
THE KNOWLEDGE ACQUISITION PROCESS IS COMPLEX AND THEREFORE IT IS MANDATORY TO DEVELOP CONCEPTS , ALGORITHMS AND TECHNIQUES TO SUPPORT THE DEVELOPMENT OF PROGRAMS AND MACHINES WHICH LEARN . THIS TASK COVERS THE IDENTIFICATION OF APPROPRIATE MODELS OF LEARNING AND THE INVESTIGATION OF LEARNING TECHNIQUES APPROPRIATE FOR AIP SYSTEMS .
LEARNING TECHNIQUES MIGHT BE BASED ON THE CAPABILITY OF THE ARTIFICIAL SYSTEM TO MEASURE ITS PERFORMANCE AND TO DEVELOP AN EVOLUTIONARY PROCESS WHICH MIGHT IMPROVE SUCH PERFORMANCE .
PROGRAMME AND INTERMEDIATE OBJECTIVES
YEARS 1 AND 2 :
- IDENTIFICATION OF MODELS ;
- DESIGN OF INTERNAL DATA STRUCTURES AND OPERATIONS FOR A PROGRAM WHICH LEARNS .
YEARS 3 AND 4 :
- INVESTIGATION OF LEARNING TECHNIQUES SUCH AS WRITING CODE OF PROGRAMS WHICH LEARN ;
- PRELIMINARY TESTING .
YEARS 5 AND 6 :
- FULL-SCALE COMMERCIALLY VALUABLE LEARNING EXPERIMENTS WITH THE PROGRAM .
TYPE B RESEARCH THEMES
RELATED TO 3.1.1 :
- APPLICATION OF EXISTING AND DEVELOPING TECHNIQUES IN COGNITIVE PSYCHOLOGY TO KBS ,
- REPRESENTATION AND USE OF GENERAL AND SPECIFIC REAL-WORLD KNOWLEDGE ,
- COMPLEXITY METRICS FOR KBS ,
- MEASURES OF COMPLETENESS , CONSISTENCY ,
- APPLICABILITY OF GENERAL MEASUREMENT THEORY ,
- WHOLE LIFE-CYCLE OF KBS ; HUMAN ACCEPTABILITY AND PRODUCTIVITY ASPECTS FOR BOTH DEVELOPERS AND CLIENTS AS WELL AS TECHNICAL PERFORMANCE ISSUES .
RELATED TO 3.1.2 :
- DIALOGUE SPECIFICATION AND ANALYSIS TOOLS ,
- NATURAL LANGUAGE SYSTEMS ARCHITECTURE ,
- APPLICATION OF EXISTING AND DEVELOPING TECHNIQUES IN COGNITIVE PSYCHOLOGY AND PSYCHOLINGUISTICS TO DIALOGUE AND NATURAL LANGUAGE PROCESSING ,
- SEMANTICS AND THE ROLE OF CONTEXT .
RELATED TO 3.1.3 :
- DIFFERENTIATION , CLASSIFICATION AND EXTENSION OF KNOWLEDGE REPRESENTATIONS FOR VARIOUS DOMAIN CLASSIFICATIONS , PARADIGMS EMPLOYED AND INFERENCE/PROCESSING MODELS USED ,
- EXPERIMENTAL APPROACHES TO KNOWLEDGE REPRESENTATION , THEIR SPECIFIC RANGES OF APPLICATION AND THEIR INTEGRATION ,
- THE RELATIONSHIPS BETWEEN KNOWLEDGE REPRESENTATION AND INFERENCE TECHNIQUES , PROBLEMS OF SELF-REFERENCE AND SYSTEM " SELF-AWARENESS " ,
- REAL-TIME INFERENCE TECHNIQUES ,
- THE ROLE OF META-KNOWLEDGE IN INFERENCE PROCESSES ,
- TECHNIQUES FOR