On Thursday, August 4, IIIM organized a workshop on self-programming in AGI systems at the Fourth Conference on Artificial General Intelligence (AGI) in Google’s headquarters, Mountain View, CA. The workshop featured presentations by seven authors on the subject of self-programming systems and a panel discussion among the participants.
Continue reading Summary of Workshop on Self-Programming, 2011 (AGI-11, Google, CA.)
Introducing a call for papers for the proposed workshop on Self-Programming in AGI Systems. The workshop will be part of the next conference on Artificial General Intelligence (AGI), hosted by Google, Inc. August 3-6th, at its headquarter facilities in Mountain view, California, USA.
A compact description of areas of interest is included in this post, and full descriptions, questions of interest, information and submission guidelines can be found on our dedicated workshop page.
Continue reading Call for Papers: Self-Programming in AGI Systems – AGI-11 Workshop
View the website for the Fourth Conference on Artificial General Intelligence
Self-Programming in AGI Systems
Call for Papers
The behavior of a computer system consists of a sequence of operations. A major difference between conventional systems and intelligent systems is that the former follow predetermined programs provided by human programmers, while the latter systems are capable of “self-programming” in the sense that their behavior is not always explicitly specified by a human, but rather “decided by the system itself” to various degrees. In a broad sense many existing AI techniques can be considered as capable of self-programming, including, for example, abilities for searching, planning, production systems, genetic programming, inductive logic programming, reinforcement learning, reactive agent/robot, adaptive agent/robot and so on. Therefore, self-programming is often achieved via learning, though there are other possibilities.
Artificial General Intelligence
The term “artificial general intelligence” (AGI) refers to general-purpose systems with an integrative and holistic intellectual and cognitive abilities. For a system to be considered AGI, some form of self-programming is necessary component, since such systems have to be capable of learning whole new skill-sets from experience, not simply improving performance on a single or a small set of pre-programmed tasks. Existing AI techniques can only achieve this to a certain degree and many problems remain unsolved. Many techniques are yet to be discovered to achieve advanced levels of system autonomy. Given the special requirements of AGI, we need to compare and evaluate alternative answers to fundamental questions related to self-programming processes.
The AGI-11 Workshop on “Self-Programming in AGI Systems” will provide an opportunity for AGI researchers to discuss these questions.