In this paper we investigate the emergence of communication in competitive multi-agent systems. A competitive environment is created with two teams of agents competing in an explo...
Michelle McPartland, Stefano Nolfi, Hussein A. Abb...
In this paper I give a brief overview of recent work on uncertainty inAI, and relate it to logical representations. Bayesian decision theory and logic are both normative frameworks...
Off-policy reinforcement learning is aimed at efficiently reusing data samples gathered in the past, which is an essential problem for physically grounded AI as experiments are us...
We present a Mutation-based Validation Paradigm (MVP) technology that can handle complete high-level microprocessor implementations and is based on explicit design error modeling, ...
In sequential decision making under uncertainty, as in many other modeling endeavors, researchers observe a dynamical system and collect data measuring its behavior over time. The...