ANTs - Autonomous Negotiating Teams
This research applies to a real-time distributed resource allocation
application involving distributed situation assessment. The hardware
configuration consists of a set of reconfigurable sensors at fixed
locations, each having local processing and low-bandwidth
communication capabilities with other sensor nodes. The objective is
to track objects moving in the environment in real-time as best as
possible, given uncertainty and constraints on sensor loads,
communication, power consumption, action characteristics, and clock
synchronization. Once the target is detected, the sensors must
communicate and cooperate so that, within a given window of time, the
data needed to triangulate the position of the target can be
collected. On this project, I constructed the high-level architecture
of our system, and developed the underlying agent framework (JAF,
below), along with specialized components for execution,
communication, directory services and resource modeling.
JAF - The Java Agent Framework
JAF was created for my Master's Thesis in computer science.
An architecture was needed for the agents working within the MASS
environment which effectively isolated the agent-dependent behavior
logic from the underlying support code which would be common to all of
the agents in the simulation. One goal of the framework was therefore
to allow an agent's behavioral logic to perform without the knowledge
that it was operating under simulated conditions, e.g. a problem
solving component in a simulated agent would be the same as in a real
agent of the same type. The framework also needed to be flexible and
extensible, and yet maintain separation between mutually dependent
functional areas to the extent that one could be replaced without
modifying the other. To satisfy these requirements, a component-based
design, the Java Agent Framework (JAF), was created.
MASS - Multi Agent System Simulator
The Multi Agent Survivability Simulator (MASS) has been developed to
provide an concrete, re-runnable, well-defined environment to test
multi-agents coordination/negociation. Our goal was to create a
distributed simulation system to test various coordination mechanisms
allowing the elements of the system to detect, react and adapt in the
face of adverse working conditions.
TAEMS - Task Analysis, Environment Modeling, and Simulation
TAEMS allows us to easily generate and use sophisticated models of a
task environment. Each model describes both high-level plan
information, as well as action interactions and low-level activity
details. I designed and implemented a Java version of TAEMS for the
MAS lab.
BIG - Bounded Information Gathering
The goal of this system is to exploit the vast amount of information
sources available today on the Internet including a growing number of
digital libraries, independent news agencies, government agencies, as
well as human experts providing a variety of services. The large
number of information sources and their different levels of
accessibility, reliability and associated costs present a complex
information gathering coordination problem. Our solution is an
information gathering agent, BIG, that plans to gather information to
support a decision process, reasons about the resource trade-offs of
different possible gathering approaches, extracts information from
both unstructured and structured documents, and uses the extracted
information to refine its search and processing activities. I worked
mainly on the low-level details of BIG, including the database
support, web interface, GUI, and a wrapper-style information
extractor.
