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Modern urban areas constitute of rich mix of mobile user devices enabled with sensors and capability of being continuously connected to existing social networking infrastructure. In future the cities can act as single sociotechnical super-organism with capability to generate large scale adaptive urban dynamics expressing various forms of urban intelligence. Such an advanced situation-aware super organism...
Negotiation is a fundamental mechanism in multi-agent systems since it allows self-interested agents to come to mutual agreements and to distribute resources efficiently and effectively. However, in competitive situations, the agents need to negotiate repeatedly with one another, thus developing mechanisms that are effective over repeated interactions is a key challenge. At present, few research work...
Swarm intelligence algorithms have been successfully applied to the detection of functional modules in PPI networks. As the increasing of the PPI network size, those algorithms will cost more time in functional module detection. In this paper, we present a novel algorithm, ACCMLF, which combines ant colony clustering with multilevel framework to reduce the runtime in the large-scale PPI networks....
This paper tackles the issue of ambient systems adaptation to users' needs while the environment and users' preferences evolve continuously. We propose the adaptive multi-agent system Amadeus whose goal is to learn from users' actions and contexts how to perform actions on behalf of the users in similar contexts. However, considering the possible changes of users preferences, a previously learnt behaviour...
The so-called Internet of Things (IoT) presents a tremendous opportunity for multitude of users to be connected to anything, whenever needed, wherever needed, by whoever needs it. Such opportunities, nonetheless, require more advanced and standardized communication interfaces to facilitate interactions between any types of "things" (smart devices, sensors, systems, networks, etc.). Recent...
Virtual training is a relatively novel field in which human beings learn to perform certain tasks by repeatedly executing them in a virtual reality environment. To make such training environments more effective, the agent paradigm has proven to be a useful tool. By conceptualising a training system as a 'virtual tutor', the system may be able to support the trainee in a similar manner as human instructors...
Decision making involves selection of a choice among alternatives. Making the right decision can be interpreted as choosing the more coherent alternative. In the context of adaptive decision making, Thagard's deliberative coherence model provides a computational model for which one is more coherent. This article presents the implementation and the integration of coherence-driven adaptive decision...
Algorithms for solving distributed constraint satisfaction problems (DisCSPs) generally assume, simplistically, that an agent represents a single variable. However, real distributed problems normally have several variables per local problem (called a complex local problem). Two major approaches of compilation and decomposition are used in solving this type of problem. In compilation, a new variable...
The task of tracing what underlies the transition from kinship tribes to nation states continues to remain an important challenge for interdisciplinary study. Multi-agent simulation can shed light on these evolutionary processes by examining the emergent social behaviour that arises from individual agent interactions. In this paper, we build a model based on existing observational and simulation studies...
This paper proposes an experimental evaluation of the communication in an Organization-based Multi-Agent System. We defined a set of criteria to evaluate the quality of interactions between agents at run time. The originalities and the advantages of our proposal are threefold: (1) the adaptation of a set of criteria and their corresponding metrics to evaluate communication in an Organization-based...
Software agents represent an evolution of traditional software, having the ability to control their own behavior and acting with autonomy. Typically, software agents act reactively, where actions and perceptions are predefined at design time, or in a deliberative manner, where the corresponding action for a given perception is found at run time through a process of reasoning. However, especially in...
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