Abstract. We propose a declarative framework for modelling multi-agent systems and specify a number of properties of these systems and agents within them. The framework is parametr...
Andrea Bracciali, Paolo Mancarella, Kostas Stathis...
Learning, planning, and representing knowledge in large state t multiple levels of temporal abstraction are key, long-standing challenges for building flexible autonomous agents. ...
In facility agriculture, it is an urgent problem to design and choose the type and facility of greenhouse based on user's requirements, which are always difficult to express c...
This paper presents a self-supervised framework for perceptual learning based upon correlations in different sensory modalities. We demonstrate this with a system that has learned...
A robotic agent must coordinate its coupled concurrent behaviors to produce a coherent response to stimuli. Reinforcement learning has been used extensively in coordinating sensin...