Colección de presentaciones al congreso CICA 2009 realizado en la Universidad de Palermo. http://hdl.handle.net/10226/266 2026-04-29T03:51:32Z 2026-04-29T03:51:32Z Durán, Orlando Perez, Luis Rodriguez, Nibaldo http://hdl.handle.net/10226/476 2015-11-24T04:09:17Z 2009-09-17T19:27:14Z

Optimization and Selection of Alternative Modular Structures using Genetic Algorithms Durán, Orlando; Perez, Luis; Rodriguez, Nibaldo In most transformations from dedicated to modular approaches, products are assumed to have a unique modular structure. However, it is well known that alternatives for constructing modular structures may exist in any level of abstraction. Explicit considerations of alternative structures invoke changes in the number of module instances so that lower capital investment in modules, more independency of structures and higher efficiency can be achieved. Relatively few research papers that deal with the optimization of modular structures problem with alternative assembly combinations aiming at minimization of module investments were found in the literature. A genetic algorithm (GA) was applied to solve the optimization problem of selecting and combining the alternative of modular structures to create a set of modular structures minimizing the cost involved in its implementation. Test results are presented and the performance of the proposed GA is compared with solutions obtained from total enumeration tests.

2009-09-17T19:27:14Z Rodriguez, Nibaldo Cabrera, Guillermo http://hdl.handle.net/10226/475 2009-09-22T18:02:30Z 2009-09-17T19:27:08Z

Wavelet Denoising Based Multivariate Polynomial For Anchovy Catches Forecasting Rodriguez, Nibaldo; Cabrera, Guillermo In this paprer, a multivariate polynomial (MP) combined with denoising techniques is proposed to forecast 1-month ahead monthly anchovy catches in the north area of Chile. The anchovy catches data is denoised by using discrete stationary wavelet transform and then appropriate is used as inputs to the MP. The MP's parameters are estimated using the penalized least square (LS) method and the performance evaluation of the proposed forecaster showed that a 98% of the explained variance was captured with a reduced parsimony.

2009-09-17T19:27:08Z Crawford, Broderick Castro, Carlos Monfroy, Eric Rodriguez, Nibaldo http://hdl.handle.net/10226/474 2009-09-22T18:56:01Z 2009-09-17T19:27:02Z

Solving Constraint Satisfaction Puzzles with Constraint Programming Crawford, Broderick; Castro, Carlos; Monfroy, Eric; Rodriguez, Nibaldo Constraint Programming (CP) is a powerful paradigm for solving Combinatorial Problems (generally issued from Decision Making). In CP, Enumeration Strategies are crucial for resolution performances. In this work, we model the known benchmark problems Latin Square, Magic Square and Sudoku as a Constraint Satisfaction Problems. We solve them with Constraint Programming comparing the performance of di erent Variable and Value Selection Heuristics in its Enumeration phase. The platform used was Mozart

2009-09-17T19:27:02Z Karanik, Marcelo J. Gramajo, Sergio D. http://hdl.handle.net/10226/473 2009-09-22T17:08:19Z 2009-09-17T19:26:43Z

Actions Combination Method for Reinforcement Learning Karanik, Marcelo J.; Gramajo, Sergio D. The software agents are programs that can perceive from their environment and they act to reach their design goals. In most cases the selected agent architecture determines its behaviour in response to different problem states. However, there are some problem domains in which it is desirable that the agent learns a good action execution policy by interacting with its environment. This kind of learning is called Reinforcement Learning (RL) and is useful in the process control area. Given a problem state, the agent selects the adequate action to do and receives an immediate reward. Then it actualizes its estimations about every action and, after a certain period of time, the agent learns which the best action to execute is. Most RL algorithms execute simple actions even if two o more can be executed. This work involves the use of RL algorithms to find an optimal policy in a gridworld problem and proposes a mechanism to combine actions of different types.

2009-09-17T19:26:43Z