This paper defines intelligence as an agent's ability to achieve goals in a wide range of environments. And authors present elegant mathematical formulation based on the concept of rewards and Kolmogorov complexity.
This paper presents Sparsey model which uses sparse distributed coding or representation (SDR) to build a hierarchical classifier. The main idea is using familarity to control the randomness of representation. But the simplication poses limited applicability.
The main idea is using an environment that resembles a preschool. I think it is an improvement over other tests such as Turing test, College Student test, or 8th grader test. But it still does not answer how the agent acquire communication skill using human language.
This paper shows an overview of AGI capabilities from developmental psychology, mathematical, physiological, and information processing perspectives. Also it discusses how to evaluate AGI using environments, tasks, and scenarios.
Intelligence is the rules to actuate actuators according to sensory input to improve one's well-being. Learning is acquiring new rules after birth. Learning requires sensors, actuators, and memory. Olfactory learning is the first learning that can give insight to the minimum parts for learning.
I was lazy and news-addict that I wanted news story that suits my interest flows towards me. I started with recommender system but soon found that it cannot deal with the delicacy of human language. I studied visual analytics to combine human intelligence with machine learning for the text analysis. But still found it unsatisfactory. Now I am studying grounded language which lead to artificial general intelligence research.