An agent-based legal knowledge acquisition methodology for agile public administration

2011 ◽  
Author(s):  
Alexander Boer ◽  
Tom van Engers
Keyword(s):  
Knowledge Acquisition ◽  
Public Administration ◽  
Legal Knowledge ◽  
Agent Based

Agent-Mediated Knowledge Acquisition for User Profiling

2008 ◽  
pp. 1486-1501
Author(s):  
A. Andreevskaia ◽  
R. Abi-Aad ◽  
T. Radhakrishnan
Keyword(s):  
Knowledge Transfer ◽  
Electronic Commerce ◽  
Knowledge Acquisition ◽  
Information Exchange ◽  
Software Agents ◽  
User Profile ◽  
User Model ◽  
User Profiling ◽  
Agent Based

This chapter presents a tool for knowledge acquisition for user profiling in electronic commerce. The knowledge acquisition in e-commerce is a challenging task that requires specific tools in order to facilitate the knowledge transfer from the user to the system. The proposed tool is based on a hierarchical user model and is agent-based. The architecture of the tool incorporates four software agents: processing agent maintaining the user profile, validating agent interacting with the user when information validation is needed, monitoring agent monitoring the effects of the changes made to the user profile, and a filtering agent ensuring the safe information exchange with other software.

scholarly journals Intelligent Agents in Co-Evolving Knowledge Networks

Mathematics ◽  
2021 ◽  
Vol 9 (1) ◽  
pp. 103
Author(s):  
Evangelos Ioannidis ◽  
Nikos Varsakelis ◽  
Ioannis Antoniou
Keyword(s):  
Knowledge Acquisition ◽  
Intelligent Agents ◽  
Diffusion Mechanism ◽  
Network Size ◽  
Agent Based ◽  
Agent Interaction ◽  
Selection Decision ◽  
Knowledge Levels ◽  
Innovation Rate ◽  
The Impact

We extend the agent-based models for knowledge diffusion in networks, restricted to random mindless interactions and to “frozen” (static) networks, in order to take into account intelligent agents and network co-evolution. Intelligent agents make decisions under bounded rationality. This is the key distinction of intelligent interacting agents compared to mindless colliding molecules, involved in the usual diffusion mechanism resulting from accidental collisions. The co-evolution of link weights and knowledge levels is modeled at the local microscopic level of “agent-to-agent” interaction. Our network co-evolution model is actually a “learning mechanism”, where weight updates depend on the previous values of both weights and knowledge levels. The goal of our work is to explore the impact of (a) the intelligence of the agents, modeled by the selection-decision rule for knowledge acquisition, (b) the innovation rate of the agents, (c) the number of “top innovators” and (d) the network size. We find that rational intelligent agents transform the network into a “centralized world”, reducing the entropy of their selections-decisions for knowledge acquisition. In addition, we find that the average knowledge, as well as the “knowledge inequality”, grow exponentially.

Hugh Heclo, “Issue Networks and the Executive Establishment”

2016 ◽  
Author(s):  
Volker Schneider
Keyword(s):  
Public Policy ◽  
Public Administration ◽  
Policy Making ◽  
Cognitive Perspective ◽  
Agent Based ◽  
Relational Perspective ◽  
Modern Politics ◽  
Issue Networks ◽  
Dynamic Perspective

This chapter comments on Hugh Heclo’s 1978 paper “Issue Networks and the Executive Establishment,” an innovative analysis of modern politics based on four analytical perspectives of public policy: an actor-centered or agent-based dynamic perspective, a relational perspective, a cultural or cognitive perspective, and a long-term perspective. Widely regarded as a classic in policy analysis and public administration, Heclo’s paper uses the concept of “issue networks” to describe the highly intricate and diversified webs of influence that shape modern American policy-making. This chapter discusses Heclo’s concept of issue networks within the context of the American situation in government and public administration, as well as its impact on fields such as political science.

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