Contextual Learning with Integrated Least Effort Knowledge Networks
In the field of artifical intelligence there are many remarkable mechanisms for learning in a specified manner but these lack the generality that is apparent in human cognition. Such generality is the problem of knowledge and most learning mechanisms improve their specialization with a flat knowledge base that’s focused in a single confined domain. This is flawed as a model of cognition because it reduces capability of both handling very complex problems and specializing in multiple domains. For this superUROP project I aim to design a contextual knowledge system and augment learning mechanisms to utilize it in a manner that reduces the intractability of hard problems and is inter-operable between distinct learning mechanisms.

How we as humans function has always had a place of interest in my mind. I intend to tackle tough problems in emulating human cognitive processes to fulfill this passion of mine. I’m excited to pursue this challenge and push myself to understand the nature of intelligence.