Supervised learning deals with the inference of a distribution over an output or label space $\CY$ conditioned on points in an observation space $\CX$, given a training dataset $D$...
From a system's perspective as opposed to an individual agent perspective, MAS adaptation is now becoming an important topic, since it can help to obtain expected outcomes ...
This paper presents Domain Relevance Estimation (DRE), a fully unsupervised text categorization technique based on the statistical estimation of the relevance of a text with respe...
In this paper, we study a particular subclass of partially observable models, called quasi-deterministic partially observable Markov decision processes (QDET-POMDPs), characterize...
In systems of autonomous self-interested agents, in which agents' neighbourhoods are defined by their connections to others, cooperation can arise through observation of the ...