Abstract-Rideshare systems allow a substantial number of people to mutually benefit from using less cars in a specific region. This would rationalize energy consumption, save money, and decrease traffic jams and pollution. However, accessibility issues have prevented these architectures from being widely spread. In this paper, we present an agent-based Rideshare system that is accessible via lightweight devices. We use auction mechanism as a method of negotiation among autonomous and proactive agents, by this we aim at accelerating agents' interactions while resolving end-user composite tasks.

Abstract-"Autonomic systems" merge advancements in the field of multi-agent software design, dynamic analysis, and decentralized control in order to assist designers in constructing complex distributed systems. Wireless Sensor Networks (WSN) represent such systems, and may benefit from autonomic system designs that target distributed nodes in diverse and changing environments that interact over a wireless communication channel for decentralized problem solving. Multi-agent system techniques have been recently applied to WSN's; however, due to hardware limitations nodes (agents) are not fully deliberative (or strong) reasoning systems. Since hardware increases rapidly it is expected that such systems may eventually be viable. In this paper we provide a generic, extensible, and deliberative simulator for testing interactions in autonomous WSN's. The belief, desire, intention (BDI) agent model of Rao is used, as well as the Agentspeak language, and the Jason framework. Results from two simple WSN test scenarios show how (simulated) BDI agents might perform basic WSN functions.

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Abstract. Ambient Intelligence (AmI) refers to an environment that is sensitive, responsive, interconnected, contextualized, transparent, intelligent, and acting on behalf of humans. This environment is coupled with ubiquity of computing devices that enables it to transparently sense context changes, to react accordingly, and even to take the initiative towards fulfilling human needs. Security, privacy, and trust challenges are amplified with AmI computing model and need to be carefully engineered. From software engineering perspective, the shift towards AmI can be seen abstractly similar to the shift from object paradigm towards agent one. Objects provide functionality to be exploited, while agents possess functionality and know how and when to use and offer it autonomously. Agent paradigm is suitable for implementing AmI considering AmI as an open complex system. Moreover, we argue that agent paradigm is equally useful for engineering all aspects of such systems from the early phases of software development life cycle.

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