Courses with Gaps

Introduction to basic programming techniques of artificial intelligence (AI); Domain analysis; representation of Knowledge and strategies; control on inference and search; development of interactive intelligence CAI programs; the role of analogical reasoning; The main contents are symbol manipulations and AI problem solving techniques; Topics include LISP primitives; LISP objects and evaluation; recursion and iteration and data abstraction (association lists; properties and DESTRUCT); macros; object-centred programming; symbolic pattern matching and basic solving methods

Review of data structures; linear data structures; hashing; trees; graphs; recursion; Complexity classes; empirical measurements of performance; time and space tradeoffs analysis; Algorithmic strategies: Brute-force algorithms; greedy algorithms; divide-and-conquer; backtracking; branch-and-bound; minimum spanning tree; heuristics; pattern matching and string/text algorithms; numerical approximation algorithms; Tractable and intractable problems

Reflection models; Texture and models; texture and environment mapping; advanced ray tracing; radiosity method; volume rendering; advanced modelling techniques; simulation and animation

The theory of quantum information and quantum computation; classical information theory; compression of quantum information; transmission of quantum information through noisy channels; quantum entanglement; quantum cryptography; classical complexity theory; quantum complexity; efficient quantum algorithms; quantum error-correcting codes; fault-tolerant quantum computation; and physical implementations of quantum computation