Kevin D. Reilly
Alan Sprague
Chrystian L Plachco
Agents and Model Abstractions in Intelligent Systems Simulations
Proc. Summer Simulation Conference, 2001
Abstract
The primary topic of this paper is agents and their potential in
simulation. We approach the elusive agent with
a postulation of working with definitions of three types, two at
empirical and theoretical poles, and others in between. Examples and
case studies are present to demonstrate contributions to model
understanding and abstraction.
Addendum:
Short case studies illustrating agents and abstractions include:
1) White and Black Boxes 2) A NN (Neural Net) Model vs a LP (Logic Programming)
Model 3)-4) Low-High Level Compartments I-II 5) Model and Its Animation
Longer case studies include 1) External Memory Strategies, with agents
as Localist NNs, as Distributed NNs, using Fuzzy Logic, using Logic Programming,
using stochastic schemes, as response evaluators (objective and subjective);
2) a load balancing task, over N nodes, K monitoring agents with (limited) observation
schedules but which share information gathering, animations of current and
task performances.
Key Words:
agents, model abstraction, neural networks, queueing