Abstract. We present a method for learning characteristic motion patterns of mobile agents. The method works on two levels. On the first level, it uses the expectation-maximization...
In this paper we introduce an object-oriented coordination language for multi-agents systems. The beliefs and reasoning capabilities ent are specified in terms of a corresponding ...
Frank S. de Boer, Cees Pierik, Rogier M. van Eijk,...
Abstract. There is currently a large interest in relational probabilistic models. While the concept of context-specific independence (CSI) has been well-studied for models such as ...
Shared mutable objects pose grave challenges in reasoning, especially for data abstraction and modularity. This paper presents a novel logic for erroravoiding partial correctness o...
Anindya Banerjee, David A. Naumann, Stan Rosenberg
This paper presents a variant of Quantum behaved Particle Swarm Optimization (QPSO) named Q-QPSO for solving global optimization problems. The Q-QPSO algorithm is based on the cha...