The trend continues in my mind spreading to other classes as well. It all started with the Markov chains in algorithmic composition. Honestly I wasn’t expecting that class was going to open up my view so much, it totally gave me that relieved feeling of finding something new and and an urge to explore it to the core.
So I want to apply these to my final PComp project, I think it could be a nice exploration through behavior-based, generative systems [the sum of actions could be generative in the end isn’t it] So let’s start by giving some informations from the sites that I have come up.
Wikipedia has a nice explanation of this. The most distinguished aspect of this-based systems are they are from bottom-up instead of top-down, which is the case with the advanced expert systems. What does that mean, so the expert system uses rules to guide the robot in task performance since behaviorr-based programs create an “artificial” behavior in the robot that causes it to autonomously perform the task required.
‘Some points; behavior based robots are more successful at task accomplishments like speech recognition, artificial vision, speech generation, complex analysis of stock market data, and life insurance policies.’
Behavior-based systems at their most basic level are neural-reflex-actions and if you put up multiple levels of those neural-reflex actions your softare becomes more intelligent. [Layered behavioral responses]