Center for Analysis and Design of Intelligent Agents

T-720-ATAI-2016

Intelligence	This course is about phenomenon we refer to as “intelligence”. A number of features of natural intelligence remain unexplained.
AGI	A number of terms have been used to refer to the various aspects that people study wrt intelligence. We use the term “artificial general intelligence” in the most general sense (no pun intended), to refer to the various aspects of intelligence that allows it to deal with variety, incompleteness, and incremental information gathering.
Advanced topics	The main focus of course is not the latest and greatest methods to come out of the field called “AI”. However, we will make some references to such methods along the way, and you may even learn something about them. But that is not what is meant by “advanced”.
What does “advanced” mean here?	It refers to advancement toward a deeper understanding of the phenomenon of intelligence.
History	The phenomenon of intelligence has been studied for ages. Some of the early notable contributions were the Greek philosophers' musings on reasoning and logic. This is not a history course, but we must make some references to the history of philosophy, AI, cybernetics and computer science along the way.

Lectures	Every week involves lectures. Listening is good. Listening and asking questions is better. Reading the assignments, listening, and asking questions is best.
Programming assignments	To enable you to get insight into principles of machine learning.
Short Essay	To allow you to delve into a topic of particular interest to you.
Programming Project	To give you a bit more in-depth experience in programming AGI systems.
Final Exam	To try to gauge how much of the material you actually understand – how much of it you have “ingested”.

Intelligence	Intelligence is a natural phenomenon.
Natural Intelligence	Many animals are considered “intelligent”.
Artificial Intelligence	Systems created by us to display (some or all) features deemed 'intelligent' when encountered in nature. Many definitions, see e.g.: .
Definitions	We must be careful when it comes to definitions – for any complex system there is a world of difference between decent definitions and good, accurate and appropriate definitions.
Aaron Sloman	“Some readers may hope for definitions of terms like information processing, mental process, consciousness, emotion, love. However, each of these denotes a large and ill-defined collection of capabilities or features. There is no definite collection of nec- essary or sufficient conditions (nor any disjunction of conjunctions) that can be used to define such terms.” (From Architectural Requirements for Human-like Agents Both Natural and Artificial by A. Sloman)

Agent	https://en.wikipedia.org/wiki/Intelligent_agent
Problem	A state that should be changed.
Goal	The resulting state after a successful change.
Task	A problem that is assigned to be solved by an agent.
Environment	The constraints that may interfere with achieving a goal.
Plan	The partial set of actions that an agent assumes will achieve the goal.
Planning	The act of generating a plan.
Knowledge	Information that can be used for various purposes.
Reasoning	The application of logical rules to knowledge.
Learning	Acquisition of knowledge that enables more successful completion of tasks.
Autonomy	The ability to do tasks without interference / help from others.

AI	In 1956 there was a workshop at Dartmouth College in the US where many of the field's founding fathers agreed on the term to user for their field, and outlined various topics to be studied within the field.
GOFAI	“Good old-fashioned AI” is a term used nowadays to describe the first 20-30 years of research in the field.
Cybernetics	Going back to WWI the field of cybernetics claimed a scope that could easily be said to subsume AI. Many of the ideas associated with information technology came out of this melting pot, including ideas by von Neumann. However, cybernetics has since all but disappeared. Why?
AGI	“Artificial general intelligence”: What we call the machine that we hope to build that could potentially surpass human intelligence at some point in the future – a more holistic take on the phenomenon of intelligence than the present mainstream AI research would indicate. Will we succeed? Only time will tell.

Isn't AI almost solved?	Short answer: No! If it's almost solved it's been almost solved for 60 years.
Should we fear AI?	Short answer: No! The threat lies with humans, not with machines – human abuse of knowledge goes back to the stone age.
Is the Singularity near?	Short answer: Who knows? By the time the course is finished you will be in a good position to make up your own minds about this.

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