1) Expert Systems

Expert Systems use domain specific knowledge, from humans who are experts in a field, to learn and emulate their behavior. Expert Systems do not rely on large data sets like machine learning; they can learn directly from humans. The system can learn all the techniques and heuristics required to match the human's level of expertise.

Expert System Algorithms We Can Design

• Alpha Beta Pruning
• Genetic Algorithms
• Uniform Cost Search
• Advanced Bi-Directional A* Search
• Simulated Annealing
• Expectiminmax
• Constraint Satisfaction Problem

Combining human knowledge and machine precision can produce a very useful AI system for businesses. Contact Us at Cyber Atlantic for a quote.

3) Machine Learning

Using a combination of the following approaches we can solve problems of overfitting, noise, and optimal prediction for your data.

Neural Networks

Artificial neural networks are designed to process data similar to a human brain. They are very powerful because they can estimate and approximate functions. Some of their benefits are:

• Use parallel distributed processing techniques
• Capabale of handling many parameters
• More parameters can be added over time
• Can work on noisy data inputs

Baynesian Learning

Uses the probabilities of each hypothesis to route from raw data to prediction. Its benefits are:

• Works with both structured and unstructured data.
• Baynes Networks are created and result in structured learning
• Unsupervised clustering, where multiple categories in a collection of objects, with unknown labels
• It can identify species, inheritances, orders
• Solved with a mixture of gaussian distribution technology

Hidden Markov Models

With Hidden Markov Models, each point consists of observable sequences of finite length. The issue is to learn the transition probabilites.

Using all of these techniques, we can implement precise Statistical Learning Methods to make your business run more efficiently with automation.