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The use of mobile devices is becoming increasingly more frequent. Although very limited, these devices now have capacities for running more advanced systems. Opportunities for developing applications using artificial intelligence have emerged with the release of APIs that are not aimed at proprietary platforms, such as J2ME. This paper discusses some approaches of artificial intelligence planni...

In this paper, planning models developed in artificial intelligence are applied to the kind of planning that must be carried out by participants in o conversation. A planning mechanism is defined, and a short fragment of o free-flowing videotaped conversation is described. The bulk of the paper is then devoted to an attempt to understand the conversation in terms of the planning mechanism. This...

1.1 Trajectory planning This chapter is a contribution to the field of Artificial Intelligence. Artificial Intelligence can be defined as the study of methods by which a computer can simulate aspects of human intelligence (Moravec, 2003). Among many mental capabilities, a human being is able to find his own path in a given environment and to optimize it according to the situation requirements. ...

This paper is based on swarm intelligence and chaotic dynamics for learning. We address this issue by considering the problem of path planning for mobile robots. Autonomous systems assume intelligent behavior with ability of dealing in complex and changing environments. Path planning problem, which can be studied as an optimization problem, seems to be of high importance for arising of intellig...

Planning is a subject of interest to the Artificial Intelligence community. Genetic algorithms, neural networks, and simulated annealing are heuristic search methods often used to solve complex optimization problems. In this paper, we have proposed a novel intelligence paradigm to solve planning problems. This paper extends the Artificial Immune System (AIS) approach by proposing a new methodol...