April 26, 2008

Influence of Artificial Intelligence on Communication Systems

Influence of Artificial Intelligence on Communication Systems

An invited talk at Snow & Avalanche Study Establishment Research & Development Center (SASE RDC), Chandigarh, on April 16, 2008, by R C Chakraborty, Visiting Prof. JIET, Guna & Former Dir. DTRL & ISSA (DRDO). The Highlights of my talk :

(a) Timeline of Telecommunication related technology – Telegraph, Morse code, Telephone Exchange, Wireless telegraphy, Iconoscope, Television system, Radio networks;

(b) Timeline of Artificial Intelligence related technology – Roman Abacus, Pascaline, Diff. Engine, Boolean algebra, Turing machines, Von Neumann architecture, ENIAC;

(c) Timeline of AI events – Turing test, intelligent behavior, Logic Theorist, Birth of AI, General Problem Solver, LISP language, DoD’s Advanced Research projects, Micro-world program SHRDLU, Expert systems, Computer vision, Prolog ;

(d) Modern digital communications – geosynchronous communication satellites, packet switching theory, wide-area computer network, Optical fiber, Internet era, ARPANET, Birth of login – ‘log’ ‘in’, Protocol – TCP/IP, Internet;

(e) AI vocabulary – Intelligence, Intelligent behavior, knowledge is collection of facts, Learning is what facts or behaviors represent, Knowledge Model – a degree of connectedness & understanding that increase, we progress from data to information to knowledge and to wisdom;

(f) Building Intelligent Communication Systems – Seamless global network, Intelligent mobile platform, Voice-recognition across Mobile-phone, and Knowledge base Networking;

(g) Conclusion – We live in an era of rapid change, moving from information to knowledge based seamless global intelligent network of society.  The creation of intelligence in machine has been a long cherished desire to replicate the functionality of the human mind. Intelligent information and communications technology (IICT), emulates and employ some aspect of human intelligence in performing a task. The IICT based systems, include sensors, computers, knowledge-based software, human-machine interfaces and other devices. Today, intelligent systems applications exists virtually in all sectors where they deliver social as well as economic benefits.

For complete lecture slides move on to Website URL :


April 3, 2008

Artificial Intelligence – Knowledge Representation – issues, predicate logic, rules

Artificial Intelligence – Knowledge Representation, Issues, Predicate Logic, Rules

This is part of the courseware on Artificial Intelligence, by R C Chakraborty, at JUET. It consists eight hours of lectures. The topics are :

Knowledge Representation (KR) – introduction, knowledge progression, model, category, typology map, relationship, mapping, representation, schemes, relational, inheritable, inferential, declarative, procedural, attributes, relationship, granularity.

KR using Logic – predicate logic, propositional logic, statements, variables, symbols, connective, truth value, contingencies, tautologies, contradictions, antecedent, consequent, argument, expressions, quantifiers, formula, representing “IsA” and “Instance” relationships.

KR using Rules – declarative, procedural, meta rules, procedural verses declarative knowledge & language, logic programming characteristics, statement, language, syntax & terminology, data components, simple & structured data objects, program components clause, predicate, sentence, subject, queries, programming paradigms, model, computation, imperative model, functional model, logic model, reasoning, forward and backward chaining, conflict resolution, and control knowledge.

For complete course lecture slides move on to Website URL :


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