Software Agents
Agent as a black box
Intelligent Agents
Human Agents (e.g. travel agent)
Hardware Agents (e.g. robot)
Software AgentsInformation Agent
Cooperation Agent
Transaction Agent
Information Agent:
support in search for information in networks.
Cooperation Agent:
complex problem solving with other agents or humans
Transaction Agent:
processing and monitoring of transactions
Characteristics of Intelligent Software Agents
Reactivity (senses environment and reacts)
True reactive (no internal environment model)
Deliberative (internal environment model)
example: Pointcast Network
Proactivity/goal-orientation
Reasoning/learning
Autonomy (follow goals by acting alone)
Mobility (move from one computer to another over a network)
Communication/cooperation
Deliberative agents
Beliefs (about environment)
Desires (judgment of future situations, may be unrealistic or contradictory)
Goals (subset of desires on which agent could act)
Intentions (subset of goals chosen to act upon)
Related areas
Artificial Intelligence (learning, reactivity, proactivity)
Distributed Artificial Intelligence (communication, cooperation)
Network comunication (communication, mobility)
Decision theory (Autonomy, learning)
Simple Search engines
Input of information: follow links
Indexing of information: syntactic analysis, storage in database
Retrieval: compare query with doc contents, rank retrieved documents
www.altavista.com , www.webcrawler.com , www.hotbot.com
Meta Search engines
Query multiple simple search engines
Aggregate results (relevance check, recognition of duplicates)
www.go2net.com (MetaCrawler)
NewsWatcher
Personalized messages and information items on the Internet
Recommender or Collaborative Filtering Agents
User interface agents
Shopping agents for comparison shopping
Agent-based marketplaces, negotiation, collaboration, auctions
Agents that transport themselves over the Internet.
Mobile network agents are programs that can be dispatched from one computer and transported to
a remote computer for execution.
Arriving at the remote computer, they present their credentials and obtain access to local services and data.
The remote computer may also serve as a broker by bringing
together agents with similar interests and compatible goals, thus providing a meeting
place at which agents can interact.
(from IBM Aglets)
A government case study: FinCEN, a system for finding financial crime.
Cash transactions over $10,000 are reported and stored in database
Database size is approx. 10M
Suspiciousness evaluation rules
Both data-driven and user-directed
GIS and link analysis & visualization tools
Key problem: Group transactions into related sets for detailed analysis
Consolidation: Matching of fields to identify all transactions involving people, businesses or accounts
Linkage: Identification of pairs of subjects and/or accounts which share a common transaction
Data mining done by humans
Future directions:
Use an agent-based approach for consolidation and linkage.
Use FinCEN's results to update the rule base.
References
Intelligent Software Agents Application and Classification Nick Moraitakis
Agent Tutorial by Pattie Maes
Software Agents for Information Retrieval Tutorial by Tim Finin, C. Nicholas, J. Mayfield