METU INFORMATICS INSTITUTE

COURSE CODE, TITLE, CREDIT, LECTURER

IS 705 – Natural Intelligence Studies (3-0)3 Mustafa Ali Türker

CATALOG DESCRIPTION

This course aims to introduce recent subject areas in Computer Science all which are somewhat related to the observation of nature by computerization. Upon gaining knowledge in these areas, presumably any artificial system can be built to better suit the natural environment it is supposed to perform in. Information systems can be equipped to handle problems or domains that are regarded as unmanageable, too complex or time-consuming.

COURSE OBJECTIVES

A great many interrelated subject areas were taken up by academical circles during the last few decades, mainly as a result of sheer amounts of information generated by the computerization of natural processes. In this course, these new areas of science will be introduced in a holistic fashion. The extension of human knowledge by the computerized observation of nature will be revealed. Hence an attempt will be made to bridge natural intelligence to the artificial and to study how we can build more intelligent systems by learning from nature.

COURSE OUTLINE, SCHEDULE & MATERIAL

Topic : Introduction to Natural Intelligence

Theme : Topic and themes of the weeks to follow will be introduced.

Coverage : 16^th and 23^rd September

Key Areas : Topics of Natural Informatics

Topic : Extelligence

Theme : Large linguistically interpreted corpora from machine learning, presentation, psycholinguistics and theoretical linguistics

Coverage : 30^th September

Key Areas : Epistemology, Evolution of visual senses, Cultural Engineering,

Social Engineering, Cultural Genes, Ontologies, NeuroLinguistic

Programming, Social Psychology, Persuasion, Mass Movements

Topic : Flux

Theme : Natural Processes do not progress like a sequential computer program, but rather “flow” in directions induced by the “observers”. Therefore, it is futile to try explaining them with ever complex formulations.

Coverage : 14^th October

Key Areas : Concept of Time, Irreversable flow of thoughts, Holism vs Causality, Irreducability vs Atomic approach, Wave-Particle Duality, Quantum Informatics, Creativity, Syncretism, Cellular Automata

Topic : The Mind

Theme : Being the observers in a Quantum Universe, how do we create flux, simply by our awareness of the universe and ourselves.

Coverage : 18^th October (To Compensate for the missing course on 1^st Week of Oct)

Key Areas : Mind over Matter, Consciousness, Theories of Mind, Emotions, Cognitive Neuroscience, Synesthesia

Topic : Learning

Theme : Learning is a relatively permanent change in mental representations or associations as a result of experience. As such it is our assimilation of observations.

Coverage : 21^st October 26^th October (As 28^th October afternoon is holiday)

Key Areas : Learning and the Brain, Cognitivism, Complex Learning and Cognition, Metacognition, Self-Regulated Learning, Study Strategies, Social Cognition

Topic : Economy of Nature

Theme : Decision theory can be viewed as a theory of one person games, or a game of a single player against nature.

Coverage : 11^th November & 19^th November

Key Areas : Game Theory, Decision Theory, Rationality, Predictability vs Uncertainty, Planning, Reasoning, Risk Understanding, Decision Making under Uncertainty, Information Theory, Organization Theory, Social Networks, Artificial Life

Topic : Symbiotic Intelligence

Theme : A major source of order in nature is symbiotic relations. Can there be such a relation between man and machine intelligence, given that these two can not mimic each other so far.

Coverage : 25^th November

Key Areas : Symbiotic Intelligence, Co-evolution of brain and language, Man-Machine Interfaces, Semiology, Turing Test, Artificial Intelligence

Topic : Evolutionary Computation

Theme : Paradigms of evolutionary computation (genetic algorithms, evolution strategies, evolutionary programming, genetic programming, classifier systems, and combinations or hybrids thereof) are used to tackle problems that are either intractable or unrealistically time consuming to solve through traditional computational strategies.

Coverage : 2^nd December

Key Areas : Evolutionary Computation, Evolutionary Game Theory, Agent-Based Modelling, Darwinian Processes, Evolutionary Psychology, Behavioral Genetics

Topic : Complex Adaptive Systems

Theme : Introducing Complex Adaptive Systems, as a general framework that capture essential aspects of Natural Intelligence which has been covered by this course so far.

Coverage : 9^th December and 16^th December

Key Areas : Chaos, Non-Linear Systems, Semantic Machines, Complex Adaptive Systems, Self-Organization, Emergence, Recursion (Strange Loops), Hypercomputation