We introduce a general framework for formalizing and analyzing the problem faced by a Decision Maker (DM) working under information-theoretic constraints on their observational ability. The random… (More)

This paper discusses the problem of extending the domain of learning sets and introduces HERBIE, a program which achieves this through graphical procedures rather than via neural networks. It is… (More)

Many machine learning problems involve predicting the joint strategy choice of some goaldirected “players” engaged in a noncooperative game. Conventional game theory predicts that that joint strategy… (More)

A powerful technique for optimizing an evolving system “agent” is co-evolution, in which one evolves the agent’s environment at the same time that one evolves the agent. Here we consider such… (More)

We extend a recently introduced approach to the positive problem of game theory, Predictive Game Theory (PGT Wolpert (2008)). In PGT, modeling a game results in a probability distribution over… (More)