ACGI respects the Application Programming Interface whilst using genetic programming to optimise the implementation of the API. It reduces the scope for improvement but it may smooth the path to GI acceptance because the programmer’s code remains unaffected; only library code is modified. We applied ACGI to C++ software for the stateof-the-art OpenCV SEEDS superPixels image segmentation algorit...

Performing policy iteration in dynamic programming should only require knowledge of relative rather than absolute measures of the utility of actions { what Baird (1993) calls the advantages of actions at states. Nevertheless, existing methods in dynamic programming (including Baird's) compute some form of absolute utility function. For smooth problems, advantages satisfy two di erential consist...

A simple design method using dynamic programming is proposed for good LDPC codes with relatively low code-rate. By applying a dynamic programming optimization to the construction of the portion fixed for easy encoding in the parity-check matrix, we can maximize the girth associated with columns contained in that portion of the matrix. Simulation results show performance improvement over the con...

Nemhauser and Trick presented the problem of nding a timetable for the 1997/98 Atlantic Coast Conference (ACC) in basketball. Their solution, found with a combination of integer programming and exhaustive enumeration, was accepted by the ACC. Finite-domain constraint programmingis another programming technique that can be used for solving combinatorial search problems such as sports tournament ...

We have de ne a network programming model called Mobile Assistant Programming (MAP) for development and execution of communication applications in large scale networks of heterogeneous computers. MAP assistants are high-level interpreted programs that can move between nodes, create clones and report results. Their execution is asynchronous and persistent to take into account client disconnectio...

In Search Based Software Engineering, Genetic Programming has been used for bug fixing, performance improvement and parallelisation of programs through the modification of source code. Where an evolutionary computation algorithm, such as Genetic Programming, is to be applied to similar code manipulation tasks, the complexity and size of source code for real-world software poses a scalability pr...

Fuel cell hybrid electric vehicles have attracted a large amount of attention in recent years owing to their advantages zero emissions, high efficiency and low noise. To improve the fuel economy system durability vehicles, this paper proposes an energy management strategy optimization method for based on dynamic programming. Rule-based dynamic-programming-based strategies are developed building...

Fitness distributions are employed as tools for understanding the effects of variation operators in Genetic Programming. Eleven operators are analyzed on four common benchmark problems by estimating generation dependent features of the fitness distributions, e.g. the probability of improvement and the expected average fitness change. Fitness Distributions: Tools for Designing Efficient Evolutio...

In this paper we used a Replication Function (R. F.) for improvement tracking with dynamic programming. The R. F. transforms values of gray level [0 255] to [0 1]. The resulting images of R. F. are more striking and visible in skin regions. The R. F. improves Dynamic Programming (D. P.) in overlapping hand and face. Results show that Tracking Error Rate 11% and Average Tracked Distance 7% reduced.

The benefits of pair programming have been recognized for some time now. Numerous attempts have been made to introduce pair programming in the classroom to improve student learning and performance. A trial introduction of this method in the introductory Computer Science (CS1) lab-based class is reported. The noticeable improvement found in student performance is in agreement with most previous ...