201,301 research outputs found
Neeko: Leveraging Dynamic LoRA for Efficient Multi-Character Role-Playing Agent
Large Language Models (LLMs) have revolutionized open-domain dialogue agents
but encounter challenges in multi-character role-playing (MCRP) scenarios. To
address the issue, we present Neeko, an innovative framework designed for
efficient multiple characters imitation. Unlike existing methods, Neeko employs
a dynamic low-rank adapter (LoRA) strategy, enabling it to adapt seamlessly to
diverse characters. Our framework breaks down the role-playing process into
agent pre-training, multiple characters playing, and character incremental
learning, effectively handling both seen and unseen roles. This dynamic
approach, coupled with distinct LoRA blocks for each character, enhances
Neeko's adaptability to unique attributes, personalities, and speaking
patterns. As a result, Neeko demonstrates superior performance in MCRP over
most existing methods, offering more engaging and versatile user interaction
experiences. Code and data are available at
https://github.com/weiyifan1023/Neeko
A Role-Based Approach for Orchestrating Emergent Configurations in the Internet of Things
The Internet of Things (IoT) is envisioned as a global network of connected
things enabling ubiquitous machine-to-machine (M2M) communication. With
estimations of billions of sensors and devices to be connected in the coming
years, the IoT has been advocated as having a great potential to impact the way
we live, but also how we work. However, the connectivity aspect in itself only
accounts for the underlying M2M infrastructure. In order to properly support
engineering IoT systems and applications, it is key to orchestrate
heterogeneous 'things' in a seamless, adaptive and dynamic manner, such that
the system can exhibit a goal-directed behaviour and take appropriate actions.
Yet, this form of interaction between things needs to take a user-centric
approach and by no means elude the users' requirements. To this end,
contextualisation is an important feature of the system, allowing it to infer
user activities and prompt the user with relevant information and interactions
even in the absence of intentional commands. In this work we propose a
role-based model for emergent configurations of connected systems as a means to
model, manage, and reason about IoT systems including the user's interaction
with them. We put a special focus on integrating the user perspective in order
to guide the emergent configurations such that systems goals are aligned with
the users' intentions. We discuss related scientific and technical challenges
and provide several uses cases outlining the concept of emergent
configurations.Comment: In Proceedings of the Second International Workshop on the Internet
of Agents @AAMAS201
A Semantic Grid Oriented to E-Tourism
With increasing complexity of tourism business models and tasks, there is a
clear need of the next generation e-Tourism infrastructure to support flexible
automation, integration, computation, storage, and collaboration. Currently
several enabling technologies such as semantic Web, Web service, agent and grid
computing have been applied in the different e-Tourism applications, however
there is no a unified framework to be able to integrate all of them. So this
paper presents a promising e-Tourism framework based on emerging semantic grid,
in which a number of key design issues are discussed including architecture,
ontologies structure, semantic reconciliation, service and resource discovery,
role based authorization and intelligent agent. The paper finally provides the
implementation of the framework.Comment: 12 PAGES, 7 Figure
Peer - Mediated Distributed Knowledge Management
Distributed Knowledge Management is an approach to knowledge management based on the principle that the multiplicity (and heterogeneity) of perspectives within complex organizations is not be viewed as an obstacle to knowledge exploitation, but rather as an opportunity that can foster innovation and creativity. Despite a wide agreement on this principle, most current KM systems are based on the idea that all perspectival aspects of knowledge should be eliminated in favor of an objective and general representation of knowledge. In this paper we propose a peer-to-peer architecture (called KEx), which embodies the principle above in a quite straightforward way: (i) each peer (called a K-peer) provides all the services needed to create and organize "local" knowledge from an individual's or a group's perspective, and (ii) social structures and protocols of meaning negotiation are introduced to achieve semantic coordination among autonomous peers (e.g., when searching documents from other K-peers). A first version of the system, called KEx, is imple-mented as a knowledge exchange level on top of JXTA
An agile business process and practice meta-model
Business Process Management (BPM) encompasses the discovery, modelling, monitoring, analysis and improvement of business processes. Limitations of traditional BPM approaches in addressing changes in business requirements have resulted in a number of agile BPM approaches that seek to accelerate the redesign of business process models. Meta-models are a key BPM feature that reduce the ambiguity of business process models. This paper describes a meta-model supporting the agile version of the Business Process and Practice Alignment Methodology (BPPAM) for business process improvement, which captures process information from actual work practices. The ability of the meta-model to achieve business process agility is discussed and compared with other agile meta-models, based on definitions of business process flexibility and agility found in the literature. (C) 2017 The Authors. Published by Elsevier B.V
Measuring the Pro-Activity of Software Agents
Despite having well-defined characteristics, software agents do not have a developed set of measures defining their quality. Attempts at evaluating software agent quality have focused on some agent aspects, like the development process, whereas others focusing on the agent as a software product have basically adopted measures associated with other software paradigms, like procedural and object-oriented concepts. Here we propose a set of measures for evaluating software agent pro-activity, the software agent's goal-driven behavioral ability to take the initiative and satisfy its goal
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A customizable multi-agent system for distributed data mining
We present a general Multi-Agent System framework for
distributed data mining based on a Peer-to-Peer model. Agent
protocols are implemented through message-based asynchronous
communication. The framework adopts a dynamic load balancing
policy that is particularly suitable for irregular search algorithms. A modular design allows a separation of the general-purpose system protocols and software components from the specific data mining algorithm. The experimental evaluation has been carried out on a parallel frequent subgraph mining algorithm, which has shown good scalability performances
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Knowledge Management for Public Administrations: Technical Realizations of an Enterprise Attention Management System
The improvement of governments’ efficiency has gained great importance and validity especially in the current times of economic downturn. E-Government constitutes the most contemporary techno-managerial proposition in the track of possible interventions. The paper addresses, more specifically, empowerments necessitated by Public Administration (PA) organizations. Anchored on the needs of three real-life cases, the paper describes the conception and the realization of an IT artefact together with its methodological appeals aiming at improving information access and delivery and thus PAs’ decision making capacity. Our proposition constitutes a novel approach for managing users’ attention in knowledge intensive organizations which goes beyond informing a user about changes in relevant information towards proactively supporting the user to react on changes. The approach is based on an expressive attention model, which is realized by combining ECA (Event-Condition-Action) rules with ontologies. The technical realizations described in the paper constitute the underlying infrastructure of an Enterprise Attention Management System
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