In multi-agent planning environments, action models for each agent must be given as input. However, creating such action models by hand is difficult and time-consuming, because i...
Applying learning techniques to acquire action models is an area of intense research interest. Most previous works in this area have assumed that there is a significant amount of...
Abstract. The brain representations of words and their referent actions and objects appear to be strongly coupled neuronal assemblies distributed over several cortical areas. In th...
Anytime algorithms, whose quality of results improves gradually as computation time increases, provide useful performance components for timecritical planning and control of robot...
This paper develops Probabilistic Hybrid Action Models (PHAMs), a realistic causal model for predicting the behavior generated by modern concurrent percept-driven robot plans. PHA...