Human intelligence requires decades of full-time training before it can be reliably utilised in modern economies. In contrast, AI agents must be made reliable but interesting in r...
Planning how to interact against bounded memory and unbounded memory learning opponents needs different treatment. Thus far, however, work in this area has shown how to design pla...
We present a novel method for information-theoretic exploration, leveraging recent work on mapping and localization. We describe exploration as the constrained optimization proble...
Argumentation is a promising approach used by autonomous agents for reasoning about inconsistent knowledge, based on the construction and the comparison of arguments. In this pape...
We introduce a novel case study in which a group of miniaturized robots screen an environment for undesirable agents, and destroy them. Because miniaturized robots are usually end...