The AGI Landscape

The AGI Landscape $\Omega$ is going to push the boundary of artificial general intelligence.

$$\mathbf{\Omega} = \underset{\theta}{\arg\max}\ \mathcal{AGI}(\theta)$$

Concepts

• Kolmogorov complexity

Frameworks

https://github.com/deepmind/pysc2

https://pythonprogramming.net/starcraft-ii-ai-python-sc2-tutorial/

Important Papers

• Universal Transformers

• The Forget-me-not Process

• AGI Safety Literature Review : summary of general safety research in agi

• Out-of-sample extension of graph adjacency spectral embedding: consider the problem of obtaining an out-of-sample extension for the adjacency spectral embedding, a procedure for embedding the vertices of a graph into Euclidean space.

• Alignment for Advanced Machine Learning Systems

• Measuring and avoiding side effects using relative reachability: introduces a general definition of side effects, based on relative reachability of states compared to a default state, that avoids these undesirable incentives.

Nov

1. The Importance of Sampling in Meta-Reinforcement Learning

2. Inequity aversion improves cooperation in intertemporal social dilemmas

Books

Probability

• R. Durrett Probability: Theory and Examples (4th edition).

• P. Billingsley Probability and Measure (3rd Edition). Chapters 1-30 contain a more careful and detailed treatment of some of the topics of this semester, in particular the measure-theory background. Recommended for students who have not done measure theory.

• R. Leadbetter et al A Basic Course in Measure and Probability: Theory for Applications is a new book giving a careful treatment of the measure-theory background.

There are many other books at roughly the same ``first year graduate" level. Here are my personal comments on some.

• D. Khoshnevisan Probability is a well-written concise account of the key topics in 205AB.

• R. Bhattacharya and E. C. Waymire A Basic Course in Probability Theory is another well-written account, mostly on the 205A topics.

• K.L. Chung A Course in Probability Theory covers many of the topics of 205A: more leisurely than Durrett and more focused than Billingsley.

• D. Williams Probability with Martingales has a uniquely enthusiastic style; concise treatment emphasizes usefulness of martingales.

• Y.S. Chow and H. Teicher Probability Theory: Independence, Interchangeability, Martingales . Uninspired exposition, but has useful variations on technical topics such as inequalities for sums and for martingales.

• R.M. Dudley Real Analysis and Probability. Best account of the functional analysis and metric space background relevant for research in theoretical probability.

• B. Fristedt and L. Gray A Modern Approach to Probability Theory. 700 pages allow coverage of broad range of topics in probability and stochastic processes.

• L. Breiman Probability. Classical; concise and broad coverage.

• O. Kallenberg Foundations of Modern Probability. Quoting an amazon.com reviewer: ``.... a compendium of all the relevant results of probability ..... similar in breadth and depth to Loeve's classical text of the mid 70's. It is not suited as a textbook, as it lacks the many examples that are needed to absorb the theory at a first pass. It works best as a reference book or a "second pass" textbook."

• John B. Walsh Knowing the Odds: An Introduction to Probability. New in 2012. Looks very nice -- concise treatment with quite challenging exercises developing part of theory.

• George Roussas An Introduction to Measure-Theoretic Probability. Recent treatment of classical content.

• Santosh Venkatesh The Theory of Probability: Explorations and Applications. Unique new book, intertwining a broad range of undergraduate and graduate-level topics for an applied audience.

• I. Florescu Probability and Stochastic Processes. Very clearly written, and with 550 pages gives a broad coverage of topics including intro to SDEs.

• Jim Pitman has his very useful lecture notes linked to the Durrett text; these notes cover more ground than my course will! Also some lecture notes by Amir Dembo for the Stanford courses equivalent to our 205AB.

Reference

1. The Books: https://www.stat.berkeley.edu/~aldous/205B/index.html, by Professor David Aldous from UC Berkeley.