57,730 research outputs found
Dispute Resolution Using Argumentation-Based Mediation
Mediation is a process, in which both parties agree to resolve their dispute
by negotiating over alternative solutions presented by a mediator. In order to
construct such solutions, mediation brings more information and knowledge, and,
if possible, resources to the negotiation table. The contribution of this paper
is the automated mediation machinery which does that. It presents an
argumentation-based mediation approach that extends the logic-based approach to
argumentation-based negotiation involving BDI agents. The paper describes the
mediation algorithm. For comparison it illustrates the method with a case study
used in an earlier work. It demonstrates how the computational mediator can
deal with realistic situations in which the negotiating agents would otherwise
fail due to lack of knowledge and/or resources.Comment: 6 page
An agent-based architecture for managing the provision of community care - the INCA (Intelligent Community Alarm) experience
Community Care is an area that requires extensive cooperation
between independent agencies, each of which needs to meet its own objectives and targets. None are engaged solely in the delivery of community care, and need to integrate the service with their other responsibilities in a coherent and efficient manner. Agent technology provides the means by which effective cooperation can take place without compromising the essential security of both the client and the
agencies involved as the appropriate set of responses can be generated through negotiation between the parties without the need for access to the main information repositories that would be necessary with conventional collaboration models. The autonomous nature of agents also means that a variety of agents can cooperate
together with various local capabilities, so long as they conform to the relevant messaging requirements. This allows a variety of agents, with capabilities tailored to the carers to which they are attached to be developed so that cost-effective solutions can be provided.
</p
Constructing a Virtual Training Laboratory Using Intelligent Agents
This paper reports on the results and experiences of the Trilogy project; a collaborative project concerned with the development of a virtual research laboratory using intelligence agents. This laboratory is designed to support the training of research students in telecommunications traffic engineering. Training research students involves a number of basic activities. They may seek guidance from, or exchange ideas with, more experienced colleagues. High quality academic papers, books and research reports provide a sound basis for developing and maintaining a good understanding of an area of research. Experimental tools enable new ideas to be evaluated, and hypotheses tested. These three components-collaboration, information and experimentation- are central to any research activity, and a good training environment for research should integrate them in a seamless fashion. To this end, we describe the design and implementation of an agent-based virtual laboratory
Towards engineering ontologies for cognitive profiling of agents on the semantic web
Research shows that most agent-based collaborations
suffer from lack of flexibility. This is due to the fact that
most agent-based applications assume pre-defined
knowledge of agentsâ capabilities and/or neglect basic
cognitive and interactional requirements in multi-agent
collaboration. The highlight of this paper is that it brings
cognitive models (inspired from cognitive sciences and HCI)
proposing architectural and knowledge-based requirements
for agents to structure ontological models for cognitive
profiling in order to increase cognitive awareness between
themselves, which in turn promotes flexibility, reusability
and predictability of agent behavior; thus contributing
towards minimizing cognitive overload incurred on humans.
The semantic web is used as an action mediating space,
where shared knowledge base in the form of ontological
models provides affordances for improving cognitive
awareness
Recommended from our members
Harnessing agile concepts for the development of intelligent systems
Traditional and current approaches to intelligent systems design, have led to the creation of sophisticated and computationally-intensive packages and environments, for a wide range of applications. This paper proposes methods with which to extend the functionality of such systems, borrowing knowledge management concepts from the field of Agile Manufacturing. As such, this paper proposes that the future of intelligent systems design should be based not only upon the continuing development of artificial intelligence techniques, but also effective methods for harnessing human skills and core competencies to achieve these aims
A Survey of Agent-Based Modeling Practices (January 1998 to July 2008)
In the 1990s, Agent-Based Modeling (ABM) began gaining popularity and represents a departure from the more classical simulation approaches. This departure, its recent development and its increasing application by non-traditional simulation disciplines indicates the need to continuously assess the current state of ABM and identify opportunities for improvement. To begin to satisfy this need, we surveyed and collected data from 279 articles from 92 unique publication outlets in which the authors had constructed and analyzed an agent-based model. From this large data set we establish the current practice of ABM in terms of year of publication, field of study, simulation software used, purpose of the simulation, acceptable validation criteria, validation techniques and complete description of the simulation. Based on the current practice we discuss six improvements needed to advance ABM as an analysis tool. These improvements include the development of ABM specific tools that are independent of software, the development of ABM as an independent discipline with a common language that extends across domains, the establishment of expectations for ABM that match their intended purposes, the requirement of complete descriptions of the simulation so others can independently replicate the results, the requirement that all models be completely validated and the development and application of statistical and non-statistical validation techniques specifically for ABM.Agent-Based Modeling, Survey, Current Practices, Simulation Validation, Simulation Purpose
- âŠ