Computer Systems Lab, Research project suggestions
- Machine learning
- Machine Learning
by
Tom Mitchell (CMU)
- Code examples - Decision trees, facial recognition with neural nets
- Chap 2 - Concept learning, version spaces
- Chap 3 - Decision tree learning - see code
- Chap 4 - Artificial neural networks, face recognition problem - see code
- Chap 6 - Bayesian learning
- Chap 7 - Computational learning
- Chap 8 - Instance based learning
- Chap 9 - Genetic algorithms
- Chap 10 - Learning sets of rules
- Chap 11, 12 - Analytical, inductive learning, Prolog (programming logic)
- Chap 13 - Reinforcement learning
- Decision trees: (example links) induction of decision trees,
tutorial,
ID3,
C4.5 tutorial and
manual page,
and Ross Quinlan
- Neural Networks,
neural network links,
example
neural network intro class
- see Tom Mitchell's specific
code and face images
- Practical Genetic Algorithms by Haupt
- Chap 2- Binary genetic algorithm and MatLab
- Chap 4 - Basic applications, word guess, melody writer
- Chap 7 - natural optimization algorithms, ant colony optimization, particle swarm optimization
- Ant Colony Optimization by Dorigo
- Chap 1 - Artificial ants and minimum cost paths
- Chap 3 - Ant colony optimization and traveling salesman problem
- Chap 6 - ACO algorithm for data network routing
- Artificial Intelligence, A Modern Approach by Russell/Norvig
- Chap 2 - Intelligent agents
- Chap 3-6 Searching, exploration, constraint satisfaction, adversarial search, genetic algorithms in the 8-queen problem, minimax trees, alpha-beta pruning
- Chap 7-10 Knowledge and knowledge representation
- Chap 13,14 - Uncertain knowledge, probabilistic reasoning
- Chap 18 - Learning, decision trees
- Chap 20, 21 - Statiscal learning methods, reinforcement learning
- Chap 24 - perception, machine vision
- Computer vision and image processing
- see Machine Vision by
E.R. Davies (Roy Davies)
- Chap 2 - Image processing operations, convolutions
- Chap 3 - Basic image filtering
- Chap 4 - Thresholding
- Chap 5 - Edge detection
- Chap 6 - Binary shape analysis
- Chap 7 - Boundary pattern analysis, template matching
- Also see - HIPR2 image processing ideas and
Sussex computer vision teach files
- Machine vision for DARPA-like autonomous vehicle
- Parallel programming
- Uzi Vishkin project at UMd parallel programming course, also see
course notes Thinking in Parallel
- see Parallel Programming by Barry Wilkinson, also
UNC Charlotte Parallel Programming group
- Chap 2 - message passing computing
- Chap 3 - embarrassingly simple parallel computations
- Chap 4 - partitioning and divide and conquer algorithms
- Chap 5 - pipelined computations
- Chap 6 - sychronous computations
- Chap 10 - sorting algorithms
- Chap 11 - numerical algorithms, matrices
- Chap 12 - Image processing
- Agent-based modeling, simulations
- Artificial life evolutionary scenario, see example
Growing Artificial Societies
and sugarscape
by Joshua Epstein and Robert Axtell
- Swarm applications
- Schelling's neighborhood
- Evolutionary game theory from netlogo
- Urban traffic simulator MASON
- Dewdney's bug world MASON
- Ant foraging MASON paper from Sean Luke, Liviu Panait
- MASON example models (scroll down)
- Simulation for the Social Scientist (see text)
- Chap 3 - System dynamics and world models, hawks, doves, and law abiders
- Chap 4 - Microsimulation of the impact of tax reform
- Chap 5 - queuing models
- Chap 6 - multi level simulation models
- Swarm Intelligence (see text)
- Chap 1 - models and concepts, game of life, cellular automata
- Chap 2 - symbols, connections, and optimizations, NK landscapes, binary optimization
- Chap 3 - views of evolution, the social organism, giai the living earth; flocks, herds, schools, and swarms - social behavior as optimization; robot societies
- Chap 4 - evolutionary computation - genetic algorithms
- Chap 5 - simulating social influence
- A New Kind of Science by Wolfram, Cellular Automata
- Chap 1-3 - world of simple programs
- Chap 4 - Systems based on numbers
- Chap 5 - Two dimensions and beyond
- Chap 7 - Mechanisms in programs and nature
- Chap 9 - Fundamental physics
- Chap 10-11 - processes of perception an analysis, notion of computation
- Breve 3D agent simulations, multi-agent systems
- Computer simulation methods - see text, also see
Computational Physics text by Landau
- Chap 2 - tools for simulation
- Chap 3 - simulating particle motion
- Chap 4 - Oscillatory systems
- Chap 5 - Few-body problems - the motion of planets
- Chap 6 - Chaotic motion of dynamical systems, hamiltonian chaos
- Chap 7 - Random processes
- Chap 8 - Many-particle systems
- Chap 9 - Numerical systems, fourier series, normal modes and waves,
- Chap 10 - Electrodynamics
- Chap 11 - Numerical and monte carlo methods
- Chap 13 - Fractals and Kinetic growth
- Chap 14 - Complex systems, genetic algorithms, cellular automata, neural nets
- Also see Scientific Computing - Symbolic, Graphic, and Numeric Modeling by Landau
- 3D Graphics in OpenGL
- Example programs from OpenGL programming guide (the "red book")
- Chap 2 - drawing geometric objects
- Chap 3 - Viewing
- Chap 4 - Color
- Chap 5 - Lighting
- Chap 6 - Blending, antialiasing, fog
- Chap 7 - Display lists
- Chap 8 - Drawing pixels, bitmaps, fonts, and images
- Chap 9 - Texture mapping
- Chap 10 - Framebuffer
- Chap 11, 12 - Tessellators and Quadrics, Evaluators and NURBS
- Computational Linguistics
- Natural Language Processing, see text by Allen
- Part 1 - Syntactic processing
- Part 2 - Semantic Interpretation
- Speech and Language Processing by Jurafsky
- Part 1 - Words,regular expressions, automata
- Part 2 - Syntax, word classes, context-free grammars, parsing
- Part 3 - Semantics
- Chap 20, 21 - Natural language generation, Machine translation
- also see Foundations of Statistical Natural Language Processing by Manning and Schutze
- Algorithms
- Introduction to Algorithms by Cormen
- Part 1 - Mathematical foundations
- Part 2 - Sorting and order statistics, heapsort, quicksort, sorting in linear time
- Part 3 - Data Structures, linked lists/stacks/queues, hash tables, binary search trees, red-black trees
- Part 4 - Advanced design and analysis techniques, matrix chain mult., greedy algorithms, huffman codes, amortized analysis
- Part 5 - Advanced data structures, b-trees, binomial heaps, fibonacci heaps
- Part 6 - Graph algorithms, breadth first/depth first, minimum spanning trees, single source shortest path, Dijkstra's, Bellman-Ford, difference constraints, Floyd-Warshall - all pairs shortest path, maximum flow
- Part 7 - Selected topics - sorting networks, arithmetic circuits, algorithms for parallel computers, matrix operations, number theoretic algorithms, string matching, computational geometry, np-completeness
- Also see Algorithms in C++ by Sedgewick
- Computer science in education