In this paper a framework “Temporal-Vector Trajectory Learning” (TVTL) for human action recognition is proposed. In this framework, the major concept is that we would like to a...
In competitive domains, the knowledge about the opponent can give players a clear advantage. This idea lead us in the past to propose an approach to acquire models of opponents, ba...
The recognition of manual actions, i.e., hand movements, hand postures and gestures, plays an important role in human-computer interaction, while belonging to a category of particu...
Marcel Martin, Jonathan Maycock, Florian Paul Schm...
Since speaker's intentions can be represented into domain actions (pairs of domain-independent speech acts and domain-dependent concept sequences) in goal-oriented dialogues,...
The paper explores a very simple agent design method called Q-decomposition, wherein a complex agent is built from simpler subagents. Each subagent has its own reward function and...