Software Agents: An Overview by Hyacinth S. Nwana and Designing Behaviors for Information Agents by Keith Decker, Anandeep Pannu, Katia Sycara and Mike Williamson

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Software Agents An Overview by Hyacinth S.
NwanaandDesigning Behaviors for Information
Agents by Keith Decker, Anandeep Pannu, Katia
Sycara and Mike Williamson

• Presenters Wendy Nikiforuk, Rui Lopes, Brad
  Jones, and Chris Kliewer
• February 10, 1999

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Software Agents - Outline

• Introduction to Agents Papers - Chris
• Typologies from Paper One - Brad
• A Framework for Information Agents - Rui
• Conclusions and the Future - Wendy

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Designing Behavior For Information Agents

• Frameworks for constructing Agents
• Behavior of basic Information Agents
• WARREN

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Software Agents An Overview

• 2 strands of Agent research
• Strand 1 1977 to 1996
• Deliberative Agents
• Macro Issues
• Research and Development
• Strand 2 1990 to 1996
• Diversification of agent types

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What is an Agent?

• No clear consensus on a definition
• The term has been over used
• Many physical forms
• A component of SW or HW capable of accomplishing
  tasks for its user.

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Creating the Classes

• Mobility
• Deliberative or Reactive
• Roles
• Primary Attributes
• Autonomy
• Learning
• Cooperation
• Secondary Attributes

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A Typology Of Agents

• Collaborative
• Interface
• Mobile
• Reactive
• Hybrid
• Heterogeneous Systems
• Smart
• Information / Internet

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Collaborative Agents

• Emphasize autonomy and cooperation.
• Whole is greater than sum of the parts.
• promises
• flexible solutions to complex problems
• problems
• based on deliberative thinking paradigm
• communication and stability issues
• unclear implementation

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Interface Agents

• Emphasize autonomy and learning.
• promises
• automation of mundane or regular tasks
• essentially an avatar
• problems
• Is learning mechanism valid, competent,
  upgradable, defined?
• needed or desired?

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Mobile Agents

• Agent is a non-static entity.
• promises
• better / more efficient use of resources
• easily coordinated and flexible asynchronous
  system architecture
• problems
• few real world examples
• typical distributed computing problems
  (transportation, security, performance, etc.)

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Reactive Agents

• No internal, symbolic environmental model.
• Relatively simple use emergent behavior.
• promises
• robust, fault tolerant, flexible, and adaptable
• problems
• unclear development methodology
• potential scalability and performance issues

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Hybrid Agents

• Combination of other agent philosophies.
• Combination is better than singular type.
• promises
• combines best of agent philosophies
• provides focused applicability of agent
• problems
• unspecified theories underlying hybrid systems
• ad-hoc design

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Heterogeneous Agent Systems

• System of different agent types.
• Focused on interoperability between agents.
• promises
• provide flexible solutions to complex problems
• provides new way approach to old problems
• problems
• communication - what language, how, etc.
• requires an standard framework

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Information Agents

• Information source in support of other agents in
  RETSINA framework
• Framework encapsulates much of the reusable
  functionality
• Not a simple API

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Functional Overview

• Three conceptual functional parts
• Current Activity And Request Information
• Local Information Database
• Problem Solving Plan Library

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Reusable Behaviors

• Approaches to Accomplishing a Goal
• Information Agent Behaviors
• Advertising
• Message Polling
• Information Monitoring
• Query Answering
• Cloning

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Agent Architecture

• Building Blocks for Agent Behaviors
• Planning
• higher level tasks broken down into lower level
  primitive actions
• Scheduling
• dynamically decides which primitive action gets
  run next

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Agent Architecture 2

• Execution Monitoring
• prepares, monitors and completes agents next
  intended action
• Local Agent Infobase
• local data store defined by an ontology, a set of
  attributes, a language, and a schema

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Odds and Ends

• Multi-Source Information Agents
• One agent assumes responsibility for many others
• WARREN
• Six? information agents
• two stock ticker agents
• news agent
• current and historical sales information agent
• company annual report agent

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What Agents Are Not

• Expert Systems
• Modules in distributed Computing
• rarely smart
• low level messaging
• run at symbol level

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Societal Issues

• For success in the future, there are several
  societal issues which must be handled
• Privacy
• Responsibility
• Legal
• Ethical
• Etiquette
• Restricting agents

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Conclusions

• Agents can work independently, but more powerful
  when they work together.
• Truly smart or intelligent agents to not exist
• Fear of agents
• Evolutionary not Revolutionary
• Can exploit diverse and distributed knowledge

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Conclusions

• Agents are not a passing fad
• agent not intelligent agent
• have papers reviewed by a colleague
• do not oversell the domain
• be critical of the progress